SC 2020 Workshop

Since joining the Lenovo Data Center Group (DCG) in August 2017, Bev Crair recently stepped into the lead role of development and quality for the Data Center Group. She brings over 30 years of expertise developing and leading teams building sophisticated, mission-critical systems that help move humanity forward.

As part of our Leadership Spotlight series, we sat down with Bev to learn more about her role, her perspective around the importance of developing technology for the future-defined data center, and her experience and advice for others related to diversity and inclusion in the workplace.

From an early age, Bev took an interest in learning more about the world and technologies that play into who we are as humans – everything from how we communicate, to how we structure societies, to how we learn and now the role of artificial intelligence (AI) and how it continues to grow in use.

As vice president of development and quality, Bev is at the forefront of major technology trends and guides her teams to truly understand and appreciate the potential to create change in the world with technology, both as individuals and through the products that they deliver. Having a diverse, multi-national team is an important facet to her approach, as she believes that we create better solutions when we bring all of who we are to the problem and integrate our whole holistic selves, as artists, technologists, and beyond.

As a teenager, Bev aspired to be a manager and was urged by role models, including her father, and a high school physics teacher to pursue a STEM education. This journey began in her undergrad studies in nuclear physics and chemical engineering, ultimately moving into computer science and math. Bev attributes her success to having these strong role models, who pushed her to grow all of her skills to help her fulfill her goal of becoming a leader.

Bev is dedicated to building great data center products that will make a difference for customers. With the data center acting as the core for much of the technology moving us forward today, her goal is to work with her team and the DCG business segments to define and build the kind of innovation needed to continue to move us forward – as people, an industry, as a company and a team.

When Bev is not at the office and working with her colleagues around the globe, Bev enjoys scuba diving around the world, riding motorcycles, following the WNBA and supporting efforts to create more diverse and inclusive communities, particularly in mentoring women and supporting our LGBTQ youth.

Bev Crair resides in Apex, NC, with her wife after recently re-locating from Phoenix, Arizona.  You can follow her on Twitter here: @bcrair.

Dr. Misbah Mubarak is a software engineer at Amazon Web Services. She received her Ph.D. and master’s degrees in computer science from Rensselaer Polytechnic Institute in 2015 and 2011, respectively. She also has experience working at Argonne National Laboratory, CERN, Switzerland, and Teradata Corporation. She was the recipient of a U.S. Fulbright scholarship and an ACM SIGSIM PADS Ph.D. colloquium award and was a finalist for Google Anita Borg scholarship.

Mubarak has authored or co-authored over 30 papers in premiere high-performance computing (HPC) venues, including the IEEE International Parallel and Distributed Processing Symposium (IPDPS) and the Supercomputing (SC) conference and the IEEE Transactions on Parallel and Distributed Systems journal. She served as the chair/co-chair of the women in HPC series of workshops at SC and International Supercomputing Conference and has served a program committee member in several notable HPC conferences.

Hai Ah is a computational physicist with a background in low-energy nuclear physics and high-performance computing. She is a co-PI of the Nuclear Structure and Nuclear Reactions DOE INCITE (Innovative and Novel Computational Impact on Theory and Experiment) project, the NUCLEI DOE SciDAC project, and worked for over six years at the Oak Ridge Leadership Computing Facility at ORNL prior to joining LANL. Hai Ah is team lead for the Trinity Center of Excellence, helping to prepare critical tri-lab ASC codes for Trinity and future architectures. She enjoys working with students and was chair of the SC Student Cluster Competition (2010, 2015), an intense undergraduate competition to prepare the next generation of HPC scientists.

Todd Gamblin is a computer scientist in the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory. His research focuses on scalable tools for measuring, analyzing, and visualizing parallel performance data. In addition to his research, Todd leads LLNL’s DevRAMP (Reproducibility, Analysis, Monitoring, and Performance) team. He is the creator of Spack, a popular HPC package management tool, and he leads the Software Packaging Technologies area in the U.S. Exascale Computing Project.

Todd has been at LLNL since 2008. He received the Early Career Research Award from the U.S. Department of Energy in 2014. He received Ph.D. and M.S. degrees in Computer Science from the University of North Carolina at Chapel Hill in 2009 and 2005, and his B.A. in Computer Science and Japanese from Williams College in 2002.

Elizabeth Bautista is Group Lead for the Operations Technology Group, the team that ensures the accessibility, reliability, security and connectivity of NERSC and ESnet (ESnet http://www.es.net) by providing a central location for problem reporting, diagnosis, data collection, escalation and resolution to maximize the scientific productivity of users. Since joining NERSC in 1999, she has worked in the Computer Operations & Network Support Group, Workstation Support as a team lead and in the Computational Systems Group as a member of the PDSF (http://www.nersc.gov/systems/pdsf/) team.  Being familiar with both center operations and system administration, she brings a unique perspective as the lead in executing tasks, developing employees and energizing change.

As a member of the Lab’s Diversity and Inclusion Council and the Computing Science Diversity, she coordinates with Human Resources to develop recruitment and retention programs that meet the strategic mission for diversity. As such she has been involved with Broader Engagement at SC, the Grace Hopper Conference and the Richard Tapia Celebration of Diversity in Computing to broaden participation for women and underrepresented minorities in STEM.

Elizabeth manages the student internship program at NERSC. She continues to explore programs that broaden the student pool and create a pipeline for recruitment and workforce development.

She previously served as the Lab delegate to the Council of University of California Staff Assemblies (www.ucop.edu/cucsa) and CUCSA Secretary. She champions staff issues and ensures that they are communicated to the UC Community and management in accordance with Regent policy.

Elizabeth is founder of Filipinas in Computing, a subgroup of Asian Women in Computing and a community of the Anita Borg Institute that bring together Filipino women in STEM and computing. They raise awareness about issues faced by Filipinas in the industry and to celebrate their success.

She has a B.S. in Computer Information Systems and an MBA in Information Technology, both from Golden Gate University in San Francisco.

Jo Adegbola has had a varied career in the tech industry, one that has taken a winding path from Management Consultant, to Game Developer, to Sr Manager of High Performance Computing for AWS. Her passion for the last 20+ years has been in building highly performant teams that enjoy working together to deliver for the customer, unlocking entertainment experiences for millions or enabling a single research scientist to make the next big discovery. Jo has been with AWS for 2 ½ years, where she heads the development group for HPC, a group responsible for the development of AWS Batch, ParallelCluster, and EFA.

As the lead for the Outreach, Diversity, and Education team in the Computational and Information Systems Lab at the National Center for Atmospheric Research, AJ Lauer directs the Summer Internships in Parallel Computational Sciences (SIParCS) program and works with her team and labmates to create outreach efforts that inspire future generations of HPC users. She earned her BA in Psychology from the University of Wisconsin – Madison and MS in Higher Education Administration. AJ is currently a doctoral candidate in the Interdisciplinary Leadership EdD program at Creighton University where her dissertation work will focus on gender and leadership in HPC.

Gokcen Kestor is a senior research scientist in the high-performance computing group at Pacific Northwest National Laboratory. Her research solves computer science challenges in HPC software, such as scalability, energy efficiency, programmability and portability. Her research is in HPC system software mainly focuses on providing performance and energy efficiency on advanced HPC systems through runtime and compiler optimizations. She has expertise in programming models, power/performance modeling, emerging architectures, compiler, and runtime systems. She is active in the HPC research community as program committee member of top-tier HPC conferences, and a co-organizer of the Women in High Performance Computing workshops. She earned a master’s degree and a doctorate in computer science from the Universitat Politècnica de Catalunya in Spain.

Brendan Bouffler has 25 years of experience in the global tech industry creating large-scale systems for HPC environments, beginning in the 90’s when he helped co-found a US-based dot-com start-up to apply extreme computing to streaming media for broadcast video environments. The company was successfully acquired (by Apple) in 2004.
He has since been responsible for designing and building hundreds of HPC systems for researchers as well as commercial and defence organizations, all around the world. Quite a number of these efforts fed the top500 list, a few that placed in the top 5.
After leading the HPC organization in Asia for a hardware maker, Brendan joined Amazon in 2014 when it became clear to him that cloud would become the exceptional computing tool the global research & engineering community needed to bring on the discoveries that would change the world for us all.
He holds a degree in Physics and an interest in testing several of its laws as they apply to bicycles. This has frequently resulted in hospitalization. He is based in London & Seattle.

Ian Foster is Director of the Computation Institute, a joint institute of the University of Chicago and Argonne National Laboratory. He is also an Argonne Senior Scientist and Distinguished Fellow and the Arthur Holly Compton Distinguished Service Professor of Computer Science.

Ian received a BSc (Hons I) degree from the University of Canterbury, New Zealand, and a PhD from Imperial College, United Kingdom, both in computer science. His research deals with distributed, parallel, and data-intensive computing technologies, and innovative applications of those technologies to scientific problems in such domains as climate change and biomedicine. Methods and software developed under his leadership underpin many large national and international cyberinfrastructures.

Professor Foster is a fellow of the American Association for the Advancement of Science, the Association for Computing Machinery, and the British Computer Society. His awards include the Global Information Infrastructure (GII) Next Generation award, the British Computer Society’s Lovelace Medal, R&D Magazine’s Innovator of the Year, and an honorary doctorate from the University of Canterbury, New Zealand. He was a co-founder of Univa UD, Inc., a company established to deliver grid and cloud computing solutions.

Dr. Patty Lopez is a Senior Platform Applications Engineer at Intel Corporation, working with customers to deliver Xeon server chip solutions that power high end data centers and mission critical applications. Prior to joining Intel in 2008, she spent 19 years as an Imaging Scientist for Hewlett Packard, creating and transferring technology in imaging into scanner, camera, and all-in-one products. She has released over fifty products and holds seven imaging patents. She earned her BS (with honors), MS, and PhD in Computer Science from New Mexico State University (NMSU). Dr. Lopez serves on the advisory boards of the Computing Research Association-Women (CRA-W), the Computing Alliance of Hispanic Serving Institutions (CAHSI), the NMSU Foundation, and the NMSU Computer Science Department. She is an emerita board member for the Anita Borg Institute, is a Distinguished Alumna for the NMSU College of Arts and Sciences. She received the Society of Women Engineer’s 2016 Advocating Women in Engineering Award, and the HENAAC/Great Minds in STEM Community Service Award in 2010. A founding member and co-chair of Latinas in Computing, a MentorNet mentor, and a member of the NCWIT Workforce Alliance, Patty has been active for the past several years on the Grace Hopper Celebration of Women in Computing Conference organizing committee, and served as the 2013 GHC General Co-Chair (Industry). Her research interests include CS education, E-textiles, and wearable computing. Her volunteer efforts are focused on building the STEM pipeline for K-16 and beyond, and creating an inclusive organizational culture in the workplace.

Cory has over 20 years of experience building and maintaining scalable technology infrastructure in a variety of different industries including scientific publishing, higher education, and digital libraries.

Driven by organizational missions that enable and enhance intellectual pursuit, he’s coordinated many technology-related projects, providing strategic leadership in systems architecture, authentication, identity management, storage, and security; and guided the development of policies, specifications, and cost models related to technology systems.

Most recently before coming to NERSC, he managed Library IT Core Services at the University of Michigan.

Dr. Toni Collis is the Director and CEO of Collis-Holmes Innovations and Chair of Women in High Performance Computing (WHPC). Toni is a strategic manager in the HPC community as well as an experienced lecturer and trainer. The focus of her work has been on enabling those without detailed training in computer science and HPC to still use supercomputers and developing a pipeline of inclusive technology leaders. As Chair and Co-Founder of WHPC Toni also developed and led training aiming to diversity the HPC workforce by providing HPC tutorials for women academics and students in Europe.

Dr. Mariam Umar is a Software Architect at Intel. Mariam earned her Ph.D. in Computer Science from Virginia Tech in Spring, 2018. Her research involves exploration and implementation of performance and energy models as well as co-design techniques for current high-performance and future exascale architectures.

Sarvani Chadalapaka is High Performance Computing Administrator with the Office of Information Technology at the University of California, Merced as well as the WHPC’s Mentoring Programme Director. In her current role at UC Merced since 2016, she enables researchers affiliated with UC Merced to use campus-wide and regional HPC resources, as well as managing the hardware and software of the campus cluster called the MERCED Cluster (NSF Award #1429783). As an XSEDE Campus Champion, she participates in Campus Champion information sharing sessions and acts as a bridge between the local campus and XSEDE resources. Every week, Sarvani facilitates a hands-on HPC clinic where users can get one-on-one help and engage in peer mentoring. Through her efforts, HPC users on campus have increased over 300% and the MERCED cluster has more than doubled its cores, while also expanding the software supported. She is a recipient of Internet2 Inclusivity Initiative Award in Recognition of Carrie Regenstein, UCCSC’s community award for Research IT, received scholarships by CEE-Broadening Participation Program for travel support to PEARC. Sarvani holds a master’s degree in electrical engineering from the University of Texas-Arlington and a bachelor’s degree in electronics and communication engineering from India. She has always been an ardent supporter of WSTEM and also participates in numerous campus community activities, such as the Polynesian dance troupe.

Bronis R. de Supinski is the Chief Technology Officer (CTO) for Livermore Computing (LC) at Lawrence Livermore National Laboratory (LLNL). In this role, he is responsible for formulating LLNL’s large-scale computing strategy and overseeing its implementation. His position requires frequent interaction with high performance computing (HPC) leaders and he oversees several collaborations with the HPC industry as well as academia. He is also the LLNL principal point of contact for the Scientific Discovery through Advanced Computing (SciDAC) program’s Institute for Sustained Performance, Energy and Resilience (SUPER), for which he leads the resilience thrust.

Prior to becoming CTO for LC, Bronis led several research projects in LLNL’s Center for Applied Scientific Computing (CASC). Most recently, he led the Exascale Computing Technologies (ExaCT) project and co-led the Advanced Simulation and Computing (ASC) program’s Application Development Environment and Performance Team (ADEPT). ADEPT is responsible for the development environment, including compilers, tools and run time systems, on LLNL’s large-scale systems. ExaCT explored several critical directions related to programming models, algorithms, performance, code correctness and resilience for future large scale systems. He currently continues his interests in these topics, particularly programming models, and serves as the Chair of the OpenMP Language Committee.

Bronis earned his Ph.D. in Computer Science from the University of Virginia in 1998, and he joined CASC in July 1998. His dissertation investigated shared memory coherence based on isotach logical time systems. His research has covered a wide range of topics, including applications of data mining techniques to performance analysis and modeling including performance modeling through non-linear regression techniques (i.e., artificial neural networks and piecewise polynomial regression), investigations into mechanisms and tools to improve memory performance, a variety of optimization techniques and tools for MPI, and several issues with OpenMP, including its memory model and tool support.

Throughout his career, Bronis has won several awards, including the prestigious Gordon Bell Prize in 2005 and 2006, as well as an R&D 100 for his leadership of a team that developed a novel scalable debugging tool. He serves on the program committees of numerous conferences and workshops. He is a member of the ACM and the IEEE Computer Society.

Research Associate, University of Sheffield, UK

Dr Mozhgan Kabiri Chimeh​ is a Research Associate/Research Software Engineer in Massive Scale Complex Systems Simulation with Accelerated Computing at University of Sheffield (Department of Computer Science), UK. She works in the area of complex system modelling using emerging high-performance parallel architectures and her speciality is in performance acceleration targeting Many-core and Multi-core architectures. Currently, she is developing the FLAMEGPU software framework which allows complex systems modelling on GPU architectures.

Previously, she worked on accelerating logic gate circuit simulation targeting heterogeneous architectures that involved optimising simulation algorithms and applying them to various parallel architectures (SIMD enabled machines, clusters, and GPUs).

Senior Software Development Manager – Amazon Web Services

Jo Adegbola has had a varied career in the tech industry, one that has taken a winding path from Management Consultant, to Game Developer, to Sr Manager of High Performance Computing for AWS.
Her passion for the last 20+ years has been in building highly performant teams that enjoy working together to deliver for the customer, unlocking entertainment experiences for millions or enabling a single research scientist to make the next big discovery.
Jo has been with AWS for 2 ½ years, where she heads the development group for HPC, a group responsible for the development of AWS Batch, ParallelCluster, and EFA.

Collis-Holmes Innovations and Women in High Performance Computing

Dr Toni Collis is the Director and CEO of Collis-Holmes Innovations and Chair of Women in High Performance Computing (WHPC). Toni is a strategic manager in the HPC community as well as an experienced lecturer and trainer. The focus of her work has been on enabling those without detailed training in computer science and HPC to still use supercomputers and developing a pipeline of inclusive technology leaders. As Chair and Co-Founder of WHPC Toni also developed and led training aiming to diversity the HPC workforce by providing HPC tutorials for women academics and students in Europe.

Brendan Bouffler has 25 years of experience in the global tech industry creating large-scale systems for HPC environments, beginning in the 90’s when he helped co-found a US-based dot-com start-up to apply extreme computing to streaming media for broadcast video environments. The company was successfully acquired (by Apple) in 2004.
He has since been responsible for designing and building hundreds of HPC systems for researchers as well as commercial and defence organizations, all around the world. Quite a number of these efforts fed the top500 list, a few that placed in the top 5.
After leading the HPC organization in Asia for a hardware maker, Brendan joined Amazon in 2014 when it became clear to him that cloud would become the exceptional computing tool the global research & engineering community needed to bring on the discoveries that would change the world for us all.
He holds a degree in Physics and an interest in testing several of its laws as they apply to bicycles. This has frequently resulted in hospitalization. He is based in London & Seattle

Theresa is a career changer. In 2009, she started her Bachelor’s program in Business Administration at the University of Mannheim and decided afterwards to pursue her Master’s degree in Business Administration, again at the University of Mannheim. In 2015, Theresa joined Bosch in the Junior Managers Program. Since 2017, she’s an IT consultant in the area of manufacturing IT, supporting different Bosch divisions to realize their IT projects in the plants. Mid of this year, Theresa will take over a new assignment in the Corporate IT of Bosch.
In her free time, Theresa spends time outside, either with horses or while running, or is organizing events for Hackerstolz e.V

Laura Schulz is responsible for strategic development at the Leibniz Computing Centre in Garching, Germany, particularly in the areas of exascale, artificial intelligence and quantum computing. Prior to joining LRZ 1 1/2 years ago, she was Director of Marketing at the HPC Innovation Center at Lawrence Livermore National Laboratory in the US.

An accomplished Sales Executive, Strategist and Manager, Martina is a creative and innovative leader, with a portfolio of skills applicable to any industry.

Her sought-after skill-set is underpinned by almost 20 years of cross-industry experience (Public Sector (Health, Justice, and Education), Retail, Financial Services, and Pharmaceuticals – to make her a valuable leader and asset to any organisation. Working internationally with some of the largest global organisations, Martina comfortably operates at the highest level in business and consistently succeeds by keeping her customers’ business outcomes as her primary objective. This has been developed and refined over many years in senior management and revenue generation roles with a number of the world’s pre-eminent software and services companies.

Martina currently leads the IBM HPC Commercial business in Europe and has been actively involved in the HPC business for the past 15 years.

TALENT STRATEGY – WHPC VICE CHAIR & WHPC’S DIRECTOR BUSINESS DEVELOPMENT

Kelly is the founder of TalentStrategy.org and is a seasoned expert in strategic affairs. Kelly works with executives and boards on diversity and governance approaches. Her clients include research and government institutions, corporations and global initiatives. Kelly develops targeted programs to improve gender equity and engage and retain diverse talent pools for a variety of industrial sectors. Kelly specializes in organizational diversity frameworks, training, assessment, and strategic affairs for external and internal relations for complex evidence-based, multi-stakeholder STEM organizations. A regular conference presenter, Kelly has chaired diversity and workforce development streams for several conferences.

Professor of Computer Science and HPC Engineer at Intel

Helena founded her first digital start-up company at the age 18, while still studying Computer Science. She started her Intel career in ´05 as an Application Engineer within the Software and Solutions Group (SSG), developing good understanding of software products and the ISV market. She moved on building a SW lab supporting internal engineering community as well as external customers. Initially starting out as a local service unit, She lastly was managing a worldwide operating SW enabling lab, supporting, with her constantly growing team, a variety of SSG and SMG (as in press and marketing support) departments along the way. She gained marketing experience during a 6 month rotation to Portland where she was responsible for the definition of an application harvesting process for scale media apps and games, definition of benefits and the design and implementations of a program for ISVs and Intel.

Since 2010 Helena was leading the HPC Market in Germany. Working with the in country resources as well as collaborating and leveraging off the central enabling, marketing, and platform teams to grow German HPC business. In 2018 Helena received the prestigious Intel Achievement Award for her contribution to HPC.

She has Doctorate in Economics (“Strategic change management in post crisis environment”) as well as formal education in Business Administration and Computer Science.

In 2018 Helena received a tenured position as a full Professor of Computer Science at her Alma Mater, the Technical University Deggendorf, where she is building a new HPC department. Helena is also the Director of the IT-Center in charge of University IT.

System Software Developer, Lawrence Livermore National Laboratory

Elsa received her PhD in computer science form Rensselaer Polytechnic Institute in 2016.

Technical & Business Development Director
Lenovo Data Center, UKI

Angelo has been in the IT industry since 1987, with twenty years in IBM and now Lenovo being preceded by time served in distribution and a fledgling PC vendor called Amstrad in the UK.  In IBM he remained primarily in the “x86 space” as a new business seller, a builder of new divisions such as the HPC and Linux business and channel leader in the UK, Paris, Zurich and in South Africa.
Moving back to the UK&I division from the EMEA Geo where he managed the solutions and MSP business and was heavily involved in the transition to Lenovo, he is now the Technical & Business Development Director focusing upon delivering customer value through relationships with key solution vendors and business partners, along with his small but perfectly formed team and valued relationships at an EMEA level.
Angelo has in the past started additional companies including a coffee company in South Africa which was then given to the employees as a method of allowing them to build a better life for themselves.  He was a Formula 1 marshal for 13 years, a motor boat skipper and poor sailor, passing through numerous interests now focuses on maintaining an ability to ski faster than his age, running and playing the guitar really badly.

Appentra Solutions and Women in High Performance Computing

Dr Toni Collis is the CBDO for Appentra Solutions, Director of Collis-Holmes Innovations and Chair of Women in High Performance Computing (WHPC). Toni is a strategic manager in the HPC community as well as an experienced lecturer and trainer. The focus of her work has been on enabling those without detailed training in computer science and HPC to still use supercomputers. Her current role at Appentra focuses on democratising access to HPC by using the new Parallware technologies to lower the barrier for academics to write and maintain parallel software. Toni is passionate about enabling a broader range of people to make effective and efficient use of HPC facilities to help further their research. As Chair and Co-Founder of WHPC Toni also developed and led training aiming to diversity the HPC workforce by providing HPC tutorials for women academics and students in Europe.

University of Sheffield

Dr Mozhgan Kabiri Chimeh​ is a Research Associate/Research Software Engineer in Massive Scale Complex Systems Simulation with Accelerated Computing at University of Sheffield (Department of Computer Science), UK. She works in the area of complex system modelling using emerging high-performance parallel architectures and her speciality is in performance acceleration targeting Many-core and Multi-core architectures. Currently, she is developing the FLAMEGPU software framework which allows complex systems modelling on GPU architectures.

Previously, she worked on accelerating logic gate circuit simulation targeting heterogeneous architectures that involved optimising simulation algorithms and applying them to various parallel architectures (SIMD enabled machines, clusters, and GPUs).

Olivia O’Sullivan

Science and Technology Facilities Council (STFC) Hartree Centre

Olivia O’Sullivan is part of the Impact and Engagement team at the Science and Technology Facilities Council (STFC) Hartree Centre. Olivia’s work demonstrates the value of the Hartree Centre’s work in HPC, data analytics and cognitive technologies to industry and academic audiences. Using both digital and traditional mediums, she highlights the ‘people behind the projects’ and focuses on the social and economic impact of the Hartree Centre’s collaborative work. Olivia has a Masters in Science Communication and her written work has been published in scientific magazines and blogs. Before joining the Hartree Centre, Olivia worked in public engagement with biomedical research, designing bespoke public involvement initiatives around dementia and musculoskeletal disease.

Alison Kennedy

Science and Technology Facilities Council (STFC) Hartree Centre

Alison Kennedy is the current Managing Director of PRACE and is Chair of the Board of Directors of the Partnership for Research Computing in Europe (PRACE). She joined the STFC Hartree Centre in the UK as Director in March 2016. The Hartree Centre provides collaborative research, innovation and development services that accelerate the application of HPC, data science, analytics and cognitive techniques, working with both businesses and research partners to gain competitive advantage. Prior to joining Hartree, she worked in a variety of managerial and technical HPC roles at EPCC for more than 23 years.

Marjolein Oorsprong

PRACE

Marjolein Oorsprong heads the communication and outreach activities for the Partnership for Advanced Computing in Europe (PRACE). With a Master in international business and languages, and more than 10 years of professional experience in international associations and project management, she leads her multi-national team of 20+ professionals, connecting PRACE with the stakeholders of the HPC eco-system.

Founder and Director, Women in HPC, EPCC at the University of Edinburgh

Toni Collis is an Applications Consultant in HPC Research and Industry, providing consultancy and project management on a range of academic and commercial projects at EPCC, the University of Edinburgh Supercomputing Centre.

Toni has a wide-ranging interest in the use of HPC to improve the productivity of scientific research, in particular developing new HPC tools, improving the scalability of software and introducing new programming models to existing software. Toni is also a consultant for the Software Sustainability Institute and a member of the ARCHER team, providing ARCHER users with support and resources for using the UK national supercomputing service as effectively as possible. In 2013 Toni co-founded Women in HPC (WHPC) as part of her work with ARCHER. WHPC has now become an internationally recognized initiative, addressing the under-representation of women working in high performance computing.

Toni is SC17 Inclusivity Chair and a member of the Executive committee for the conference. Toni is also a member of the XSEDE Advisory Board and has contributed to the organization and program of a number of conferences and workshops over the last five years including as an Executive Committee member of the EuroMPI 2016 conference and leading over ten WHPC workshops around the world.

HPC Security Expert, Department of Defense, USA

Before returning to her software roots as the HPC Software and Test Technical Director, Lee spent many of her 30 years within the Department of Defense as a technical expert in the Information Assurance field. In her current role, she has combined both areas of expertise to address the need for stronger yet performance friendly HPC security solutions.

Program Manager, Purdue University’s Rosen Center for Advanced Computing (RCAC) & Coordinator, XSEDE Campus Champions

Marisa Brazil is an outreach and broader engagement professional with over 10 years of experience in the higher education research community that utilizes HPC resources. Marisa has a dual-role as Program Manager at Purdue University’s Rosen Center for Advanced Computing (RCAC) and Coordinator of the NSF-funded XSEDE Campus Champions program. As Program Manager at Purdue’s RCAC, Marisa manages the Purdue Women in HPC program and as well as various social media, marketing, and outreach projects for the department. As Campus Champions Coordinator, she oversees a community-based program that connects and supports more than 400 cyberinfrastructure professionals who help their researchers identify and use the computational resources that best fit their needs. Marisa is part of the leadership team that coordinates the Champions broader engagement, sustainability and strategic planning efforts and manages the marketing and communications for the program.

Marisa received her B.A. in International Relations from the American University and her M.A. in Nonprofit Leadership and Management from Arizona State University. Prior to joining Purdue and the Campus Champions, Marisa worked at a variety of higher education and nonprofit institutions including Arizona State University, George Washington University, the National Education Association, IEEE Computer Society, and the American Heart Association.

Marisa possesses a long-held interest in championing and bringing awareness to diversity and inclusion and has spent the latter part of her career supporting this effort in the HPC and technology sectors.

Applications Consultant at EPCC, University of Edinburgh

Nick Brown is an applications consultant at Edinburgh Parallel Computing Centre (EPCC) at the University of Edinburgh specializing in developing large scale HPC codes, parallel programming language design, and compilers. Nick is a STEM ambassador, is heavily involved with EPCC’s outreach program and with experience in engagement targeted toward school children (K-12.) He has also developed a number of successful public engagement activities from dinosaur racing, where the public can design their own dinosaurs which are then simulated and raced against each other to see who can create the fastest dinosaur, to the “design your own supercomputer” web-app where the public can create a supercomputer within a certain monetary and power budget to see who can execute the most operations within a certain timeframe. Nick is also heavily involved with teaching, developing courses, and supervising students, both on EPCC’s Masters program and also external training courses.

Southern California Earthquake Center (SCEC)

Scott Callaghan is a software developer at the Southern California Earthquake Center (SCEC) at the University of Southern California (USC). His research focuses on large-scale probabilistic seismic hazard analysis and the use of workflow technology in scientific applications. Scott received his master’s degree in High Performance Computing from USC in 2007.

Scott has a strong interest in encouraging awareness of and retention in HPC through education, outreach and mentoring. He explains HPC concepts through plastic balls in public outreach events in his hometown of St. Louis, and has served on the board of the SIGHPC Education chapter. Since 2011 he has been a staff member of the International HPC Summer School, and has served on the planning committee and as chair of the mentoring committee since 2014, supervising a formal mentoring program. For over ten years he has mentored undergraduate interns as part of the SCEC Undergraduate Summer Experience in Information Technology (UseIT), helping them to develop visualization software for seismic datasets and introducing a diverse group of students to HPC concepts.

Outside of work, Scott likes to play with his two-year-old son, curl, and knit.

Vice President and General Manager of the Technical Computing Initiative (TCI) in Intel’s Data Center Group

Trish Damkroger is Vice President and General Manager of the Technical Computing Initiative (TCI) in Intel’s Data Center Group. She leads Intel’s global Technical Computing business and is responsible for developing and executing Intel’s strategy, building customer relationships and defining a leading product portfolio for Technical Computing workloads, including emerging areas such as high performance analytics and artificial intelligence. This includes traditional HPC, workstations, processors and co-processors, and includes all aspects of solutions including industry leading compute, storage, network and software products. Ms. Damkroger has more than 27 years of technical and managerial roles both in the private sector and within the United States Department of Energy, most recently as the Associate Director of Computation (Acting) at Lawrence Livermore National Laboratory leading a 1,000 person group that is one of the world’s leading supercomputing and scientific experts. Since 2006, Ms. Damkroger has been a leader of the annual Supercomputing Conference series, the premier international meeting for high performance computing. She was the SC14 General Chair in New Orleans and has held many other committee positions. She was named one of HPCwire’s People to Watch in 2014. Ms. Damkroger has a master’s degree in electrical engineering from Stanford University.

Oakridge National Laboratory

Director of Visualization & Senior Research Scientist

Kelly Gaither is the Director of Visualization, a Senior Research Scientist, and the interim Director of Education and Outreach at the Texas Advanced Computing Center (TACC) at The University of Texas at Austin. Dr. Gaither leads the visualization activities while conducting research in scientific visualization, visual analytics and augmented/virtual reality. She received her doctoral degree in Computational Engineering from Mississippi State University in May, 2000, and received her masters and bachelors degree in Computer Science from Texas A&M University in 1992 and 1988 respectively. Gaither has over thirty refereed publications in fields ranging from Computatational Mechanics to Supercomputing Applications to Scientific Visualization. She is currently a co-PI and the director of Community Engagement and Enrichment and for Extreme Science and Engineering Discovery Environment (XSEDE2), a $120M project funded by the National Science Foundation. She has given a number of invited talks and keynotes. Over the past ten years, she has actively participated in conferences related to her field, specifically acting as general chair IEEE Visualization 2004 and general chair of XSEDE16.

Chief Analyst and Senior Director of Market Intelligence, Intel Data Center Group

Debra is the Chief Analyst and Senior Director of Market Intelligence for Intel’s Data Center Group. Debra’s nearly 30 year career in High Performance Computing started at IDC where she spent 17 years leading the company’s presence in high end computing in government, academia and industry. She was instrumental in driving science and technology policy initiatives in the US and abroad, highlighting the impact and importance of HPC as a fundamental economic and innovation driver. She led IDG’s initiatives in healthcare and life sciences, launching Bio-IT World magazine and Expo, the Life Sciences Venture Fund and a research advisory and consultancy.

Following IDC, Debra was VP of Strategy for IBM’s Deep Computing organization, leading such initiatives such as IBM’s Blue Gene program and the early hosted HPC solutions of Deep Computing on Demand. She ran strategy and Market Intelligence for IBM’s System and Technology Group business unit driving critical BI and analytic programs and new modeling methodologies.

Debra was CEO of Tabor Communications, expanding the scope of the company beyond HPCWire, launching a Research organization, and building out a digital delivery platform. Following Tabor, Debra was at Microsoft leading strategy and evangelism, launching its Technical Computing Executive Advisory Council and driving several high profile collaborations with key partners including the Gates Foundation, UN, DoD, and NetHope.

Since joining Intel, Debra has led the company’s efforts on multiple fronts, including expanding the use and adoption of high performance computing into new markets and communities and driving strategy and pathfinding for Intel’s Technical Computing Group. In her current role as Chief Analyst and Sr. Director of MI, she is responsible for leading the vision and technical infrastructure around developing a world class MI organization for DCG.

She is actively involved in STEM policy initiatives and in working with global organizations to advance economic development through access and use of leading edge technologies. Outside of Intel Debra is active in the community sitting on several boards. She is a devoted mom and an avid skier. .

Lawrence Livermore National Laboratory

Elsa is an application I/O specialist and systems software developer within the Livermore Computing supercomputing center at Lawrence Livermore National Laboratory. She received a Ph.D. in Computer Science from Rensselaer Polytechnic Institute, Troy, NY. Her research interests include software tools for understanding application performance throughout the I/O stack, application checkpointing, and parallel discrete-event simulation.

Acting Lead of the User Engagement Group

Rebecca Hartman-Baker is the acting leader of the User Engagement Group at the National Energy Research Scientific Computing Center at Lawrence Berkeley National Laboratory. She is a computational scientist with expertise in the development of scalable parallel algorithms for the petascale and beyond. Her career has taken her to Oak Ridge National Laboratory, where she worked on the R&D100-award winning team developing MADNESS and as a scientific computing liaison in the Oak Ridge leadership computing facility; the Pawsey Supercomputing Centre in Australia, where she coached two teams to the Student Cluster Competition at the annual Supercomputing conference and led the decision-making process for determining the architecture of the petascale supercomputer; and NERSC, where she is responsible for NERSC’s engagement with the user community to increase user productivity via advocacy, support, training, and the provisioning of usable computing environments. Rebecca earned a PhD in Computer Science, with a certificate in Computational Science and Engineering, from the University of Illinois at Urbana-Champaign.

Argonne National Laboratory

Misbah Mubarak is a postdoctoral researcher at Argonne National Laboratory. At Argonne, she is part of the data-intensive science group that is working to enable researchers make use of their big data in new scientific advances. . She is the recipient of U.S. Fulbright scholarship, ACM SIGSIM PADS PhD colloquium award and a finalist for Google Anita Borg scholarship. Misbah received her PhD and Masters in computer science from Rensselaer Polytechnic Institute (RPI) in 2015 and 2011 respectively. She also has experience working at CERN, Switzerland and Teradata Corporation.

Misbah has authored or co-authored over 25 papers in the area of performance modeling and analysis for High-Performance Computing. She has served as a peer reviewer for a number of journals including ACM Transactions on Modeling and Simulation, ACM Transactions on parallel computing and IEEE journal of computers. She has served as the technical program committee member of ACM SIGSIM PADS conference in 2016 and 2017, publicity chair for ACM SIGSIM PADS in 2017 and organizing committee member of the women in HPC workshop at Supercomputing (SC) 2016.

Kelly Nolan is a highly respected bilingual communications, marketing, and public affairs executive, with more than 12 years of experience in the education, health, economic development sectors including working closely with boards of directors, executives, government officials and elected officials, directing teams, and managing division and organizational budgets. Kelly has directed, developed and executed bold and innovative public relations, marketing, and communications strategies, including larger scale social media and internet marketing initiatives, membership and sponsorship programs for all knowledge economy sectors. She is an accomplished professional with an exceptional track record of building positive relationships with senior government officials, external partners, executives, media, clients, external agencies, and internal team members.

Research Faculty, Center for Education Integrating Science, Mathematics and Computing (CEISMC) at the Georgia Institute of Technology

Lorna Rivera serves as a Research Scientist II in Program Evaluation at the Georgia Tech Center for Education Integrating Science, Mathematics and Computing (CEISMC). Her work focuses on the intersection of scientific content, pedagogy, and equity with the goal of being both methodologically innovative and socially responsible. Rivera has conducted evaluations primarily funded by the National Science Foundation’s Division of Advanced Cyberinfrastructure. This has led her to work with over 18 universities as well as multiple international high performance computing centers and organizations such as Compute Canada, EPCC, NCSA, PRACE, RIKEN, and XSEDE. Rivera received both her Bachelor of Science in Health Education and her Master of Science in Health Education and Behavior from the University of Florida. Prior to joining Georgia Tech, Rivera worked with various institutions, including the University of Illinois at Urbana-Champaign, March of Dimes, Shands HealthCare, and the University of Florida College of Medicine. Her research interests include the evaluation of innovative programs and their sustainability.

Investigating and improving the scalability of task-based programming models

As the classical technology scaling ended (processor clock rates are not growing anymore), performance increase has to be gained from explicit parallelism. The modern computing is cheap and massively parallel, while energy and performance costs are impacted by data movement: a chip of a flagship supercomputer is expected to have soon thousands of cores on it; the energy cost for computation is decreasing much faster than the energy cost for moving data on a chip, thus the latter is becoming a top priority in order to have computing efficiency. Current HPC applications have to be ready for the Exascale era, and if current parallel programming models do not totally support constructs that describe data locality and affinity, but future Exascale programming models have to.

This work focuses on investigating data-locality sensitivity of different scientific programs written in three task-based programming models – Cilk, OpenMP, and Qthreads. The concept of data locality implies the probability of a memory reference being “local” to prior memory accesses. Among parallel programming models for shared-memory machines, the use of task-based programming models is becoming more and more common. Task-based approach refers to designing a program in terms of “tasks” – a logically discrete section of work to be done.

The goals of this work were to port these task-based codes into locality-oblivious and locality-aware task-based programming models, to compare performance between such models and to analyze task- based parallelism and data-locality sensitivity features. This study is based on the measurements from different hardware performance counters during the local and remote memory accesses within one shared-memory node.

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Author Biography

Dana Akhmetova gained her first degree at the Department of Computer Science at Lomonosov Moscow State University in 2007. She started postgraduate studies at the PDC supercomputing center in Stockholm and is now a fourth year Ph.D. student at the Department of Computational Science and Technology at the KTH Royal Institute of Technology under the supervision of Professor Örjan Ekeberg. During 2015 Dana was a Ph.D. intern at the Pacific Northwest National Laboratory in the United States, where she was focusing on task-based programming models and analysing the connection between the granularity of application tasks and the scheduling overhead in many-core shared-memory systems. Currently Dana is working on two large Exascale EC-funded projects called INTERTWinE and AllScale. The INTERTWinE project addresses the problem of programming model design and implementation for Exascale computing. The AllScale project is proposing an environment for the effective development of highly scalable, resilient and performance-portable parallel applications for future Exascale systems.

Promoting Diversity in HPC at Purdue University

This abstract highlights Purdue University’s Res earch Computing broader engagement initiative to promote and advance diversity in High Performance Computing (HPC) with emphasis on gender as well as the variety of skills, experience and culture of the women on our team. We will describe the expertise that our female team members provide to Purdue’s HPC users as well as present an update of our “Women in HPC” initiative. Our work is highlighted below:

1. Increasing Workforce Diversity: Purdue University recognizes that supporting increased diversity in a specialty field like HPC will improve the candidate pool for HPC centers and is committed to advancing the representation of women in HPC. Since 2011 Research Computing has doubled the number of women hired to the team which includes 11 females.
2. Promote Participation in HPC: An initiative to promote diversity in HPC was developed in the Fall of 2016 in the form of the Women in HPC (WHPC) networking group. Currently, we have 112 registered undergraduate, graduate, staff and faculty members. The WHPC program goal is to encourage women to pursue research and careers in HPC and technology fields. Activities include regular meetings presenting technical HPC-related topics, the promotion of technical conferences (e.g. PEARC, Grace Hopper and SC) by providing partial funding for women to attend, and the development of a mentorship program to support the growth of a vibrant HPC community and broaden access to HPC for women in sciences.

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Author Biography

Gladys is currently a Senior Scientific Applications Analyst in Research Computing at Purdue University. While providing computing expertise to students, staff and faculty with her advanced knowledge of bioinformatics software, analysis, and pipelines, she also provides instruction related to Unix and HPC – both in standalone workshops and as a lecturer in academic courses. With other female members of the Research Computing team, she founded the first Purdue’s Women in HPC program. Gladys actively participates with student-mentor programs at Purdue as well as in academic and professional
conferences. In addition, she serves as editor for a peer- reviewed journal in her research field.
An entomologist by training, her doctoral work integrated computational bioinformatics and high-performance computing techniques from the ground up. With a passion for both learning and teaching, Gladys helps guide the next generation of researchers as a computational life sciences specialist for Purdue’s Research Computing.

Framework for Planning, Executing and Monitoring Cooperating Computations

Computational simulations are considered to be the third pillar of science. To study complex phenomena such as forest fires, weather forecast or fluid dynamics, we need to precisely describe all the processes and communication under the hood.

Computational simulations are usually very demanding on computational performance and storage. According to the computational requirements of each process, the whole computation may be distributed over diverse computational facilities.

Big supercomputing centres offer both sufficient amount of computational power and disk space, however, the computing infrastructures are growing in parallelism and becoming more diverse. This heads towards very sophisticated computational techniques to take the full advantage of the machine power. Furthermore, advanced knowledge of supercomputer’s architecture and submission systems is required by users. Such a big human effort can become a bottleneck because a non-negligible number of person hours has to be invested daily, especially, if the user is not an IT specialist. My research focuses on the development of the dispatch server as a tool providing an automated planning, executing and monitoring cooperating computations. The dispatch server is inspired by the HPC as a service paradigm. Its modular design enables extensibility and unifies the access to different HPC systems through a simple client-server interface and standard web services. The dispatch server also detects the possibility of concurrent execution and offers a level of fault tolerance.

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Author Biography

Marta Čudová is a PhD student at the Faculty of Information Technology, Brno University of Technology. She received her MSc in Computer Science from the Brno University of Technology in 2016. In 2016, she attended PRACE Summer of HPC and spent two months at Edinburgh Parallel Computing Centre in the UK where she worked under Dr. Neelofer Banglawala. She also received the HPC Ambassador Award within PRACE Summer of HPC. Now, she is a member of the Supercomputing Technologies Research Group where she focuses on cluster management systems and multiphysics model coupling. This group closely collaborates with the Biomedical Ultrasound Group at University College London.

HPC Job Performance at Purdue University

This poster will present the current state of ormajob and system metrics from analysis of jobs running on the high-performance resources at Purdue University.

Because of the increasing demand of research computing resources, it is important for IT staff and users to understand their jobs’ performance characteristics. The goal of this work is to analyze the data generated by TACC Stats and Open XDMoD, and apply that data to guide decision-making around Purdue’s HPC systems.

TACC Stats and Open XDMoD are tools to provide metrics about the jobs running on the HPC resources. TACC Stats provides job- level system data and Open XDMoD presents a summary of the system’s usage statistics, as well as easy-to-use interfaces to further break down that data. Currently, TACC Stats at Purdue University records various statistics, including Memory Bandwidth, Memory Usage and CPU User Fraction on job-level basis. Using Jupyter Notebooks and python scripts, we have developed tools to analyze system usage and job-level data, and use that data to make data-driven decisions around system design and procurement.

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Author Biography

Jieyu Gao joined the Emerging IT Leaders program upon her graduation from Purdue’s Applied Statistics and Economics (Honor) program in 2016. She works with research computing users to solve data analysis problems. She is responsible for doing data analysis using Tacc Stats data and installing Open XDMoD at Purdue University.

Jieyu is one of the Gender-Diversity Award winners at Internet2 Global Summit 2017.

Addressing the skills shortages in HPC: reporting on experience of running college and university courses using sustainable HPC resources

HPC technologies and the national e-infrastructure are vital for advancements in science, business and industry. However, there is a shortage of HPC skilled staff: HPC architects, administrators, researchers and research software engineers. Currently, HPC skills are acquired mainly by students and staff taking part in HPC-related research projects.

To address the issue of skills shortages in the HPC it is essential to provide teaching and training as part of both postgraduate and undergraduate courses, and to engage with young children and college level students through inspirational outreach events.

Higher and Further Education (H/FE) institutions have a fundamental role in the development of all the people who participate in the national e-infrastructure. The design and development of such courses is challenging since the technologies and software in the fields of large scale distributed systems such as Cluster, Cloud and Grid computing are undergoing continuous change.

Current solutions from large universities and well-funded research organizations are not easily applied to Higher and Further Education. In this presentation we report on 10 years’ experience in the development of HPC related courses, and providing affordable and sustainable resource solutions for teaching and research in small to medium-size universities. We utilize already available resources at the institutions and open-source solutions whenever possible. Using COTS hardware and free open-source software in teaching HPC related topics demonstrates that H/FE institutions do not require expensive national and international supercomputer resources to deliver HPC teaching and training.

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Author Biography

Dr Violeta Holmes leads the High Performance Computing (HPC) Research Group at the University of Huddersfield. Her research interests and expertise are in the areas of HPC Systems Infrastructure, Energy Efficient Computing, Cloud Computing, Big Data, and Internet of Things. Her career in Higher Education as a researcher and lecturer in computing and engineering spans over 25 years.

In her role as ARCHER champion she supports activities to broaden the UK HPC user base to new disciplines and communities, and promotes the links between HPC users, developers and researchers across various research groups and institutes at the University of Huddersfield.

Dr. Holmes worked with 3M Buckley Innovation Centre at the University of Huddersfield in deploying HPC research and development facilities for SMEs and industry, and was HPC academic lead in the Innovate UK (TSB) funded Energy Efficient Computing project at the University of Huddersfield.

As a Chartered Engineer and the IET and BCS member, she supports the advancement and promotion of the careers of women in Science, Technology, Engineering and Mathematics (STEM), Higher Education and research.

Implementation of a meshless MLS scheme for simulations of suspension flows

This poster will focus on a meshfree method for simulations of neutrally buoyant, non-Brownian particles in Stokes flow. We will demonstrate a meshless scheme using Generalized Moving Least Squares (GMLS) polynomial reconstructions to provide a computationally efficient method with higher order accuracy for use with general boundary conditions and arbitrary polynomial shapes while maintaining stability. The emphasis will be on applications to dense suspensions of colloids, especially colloids with polydispersed sizes and non-spherical shapes. GMLS for Stokes flow has been implemented in serial in two dimensions for several colloids, however the computational demands in three dimensions require high performance computing and efficient preconditioners to handle more than one colloid. This work is in collaboration with Sandia National Laboratories, and is implemented using the Trilinos scientific computing packages Tpetra, Kokkos, and Belos to allow large-scale simulations.

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Author Biography

Amanda Howard is a Ph.D. candidate at Brown University in the Division of Applied Mathematics. Her research focuses on scientific computing and numerical methods in computational fluid dynamics, particularly applied to suspension flows of non-Brownian particles, as well as efficient implementation of higher order meshless methods. She is a recipient of a 2014 National Science Foundation Graduate Research Fellowship. At Brown, she founded the Brown University student chapter of the Association for Women in Mathematics and runs the Applied Mathematics undergraduate-graduate mentoring program.

Localized Fault Recovery for Nested Fork-Join Programs

Nested fork-join programs scheduled using work stealing can automatically balance load and adapt to changes in the execution environment. In this work, we design an approach to efficiently recover from faults encountered by these programs. Specifically, we focus on localized recovery of the task space in the presence of fail-stop failures. We present an approach to efficiently track, under work stealing, the relationships between the work executed by various threads. This information is used to identify and schedule the tasks to be re executed without interfering with normal task execution. The algorithm precisely computes the work lost, incurs minimal re- execution overhead, and can recover from an arbitrary number of failures. Experimental evaluation demonstrates low overheads in the absence of failures, recovery overheads on the same order as the lost work, and much lower recovery costs than alternative strategies.

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Author Biography

Dr. Gokcen Kestor is a research scientist at the Oak Ridge National Laboratory (ORNL) in the The Computer Science Research group. Gokcen earned her Ph.D. in Computer Science from the Polytechnic University of Catalonia (UPC) in 2013, Barcelona. Her dissertation investigated effective software transactional memory solutions.

Her research interests include resilience for future large scale systems, parallel programming models and runtimes, especially task based programming models, compilers, power and performance analysis and modeling of HPC applications and emerging technologies, investigations into effective use of emerging memory technologies and machine learning techniques in the context of HPC.

She is currently working on fault tolerance solutions for distributed task-programming models, configurable soft error detection techniques, and evaluation of emerging memory technologies.
She is a member of the ACM and IEEE Computer Society.

ElementaryPi : Elementary Kids Learning How To Make Raspberry Pi Cluster

Kids aren’t instructed in learning computer science and this project will change that. I have created steps for elementary kids to make themselves a cluster. In this project. I have made interface for parallel visualization with Visit. At the end, I have made a step by step website for kids to learn about parallel computing that includes software tools to complete the project.

Author Biography

My name is Camdyn Leidel and I am eleven years old. I play Softball and participate in Girl scouts. I got into computer science after my father became entrepreneur. I started asking questions about computer science, and he showed me the Woman HPC group. Afterwards, I started working on this project and traveled to Germany for ISC. I met a lot of people and now I’m ready for SC.

Women in IT Networking at SC (WINS)

Women in IT Networking at SC (WINS), an NSF funded program, is a collaboration between the University Corporation for Atmospheric Research (UCAR), the Department of Energy’s Energy Sciences Network (ESnet) and the Keystone Initiative for Network Based Education and Research (KINBER) that fosters gender diversity in the research and education (R&E) community’s network and computer systems engineer occupations. The Supercomputing Conference’s SCinet organization offers a unique opportunity for intensive hands-on training and workforce development in networking, security, measurement, computer systems and research support. Although some small number of women have been members of SCinet since its earliest days, WINS was launched to increase the diversity of the SCinet volunteer staff and provide professional development opportunities to highly qualified women in the field of networking and computing and provide community building for women who pursue careers in networking and Cyberinfrastructure (CI). Experience shows that SCinet participants also grow in their ability to build collaborative relationships and develop long-term professional relationships, which open the door to future career opportunities. The primary goal of the project is to give U.S. women professionals in their early to mid-career the opportunity to build expertise and business connections, while at the same time fostering diversity in the overall network and computer systems engineering workforce. Another valuable outcome is raising awareness of the lack of diversity in IT and the value of diverse activities.

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Author Biography

Marla Meehl is Section Head of the Network Engineering and Telecommunications Section (NETS) at the University Corporation for Atmospheric Research (UCAR), where she routinely manages a budget of $4M, a staff of 25, and multiple large-scale networking projects. She has 20 years of experience managing large network projects. For the past 18 years, she has managed large external networking projects and activities for UCAR, including the Front Range GigaPoP (FRGP), Bi-State Optical Network (BiSON), and the Boulder Point of Presence (BPoP). Meehl has a strong relationship with the regional research and education community, including the Western Regional Network (WRN), and has been leading the efforts of Westnet for over 15 years. Meehl is also the Principal Investigator (PI) of the National Science Foundation-funded “Women in IT Networking at SC” (WINS) project. She is also the Co-Chair of the Internet2 Gender Diversity Initiative.

Best Practices for Scalable Visualization

Our study attempts to balance the performance of machine learning and scientific visualizations using In-Situ visualization. We used ParaView Catalyst and OspRay (ray tracing based renderer) to perform the parallel processing and the high- fidelity visualization of large-scale simulations such as Direct Numerical Simulation (DNS) turbulent flow simulation.

We had 100 frames of (“coarse”) data with 3 velocity components and pressure are stored in the database.

The main goal of our study was to classify the vorticity of the flow and represent different clusters in a 3D visualization.

We generated the vorticity vector, which is the curl of the velocity then applied KMeans clustering algorithm to classify the data set into 3 clusters. OspRay was enabled in ParaView to achieve high-finality rendering. After designing the visualization pipeline we used ParaView Catalyst to generate the script that can be used later for the in-situ visualization. Visualization pipeline design and the script generation were carried out on TACC’s Stampede2 using one node with 64 processors (Intel Xeon Phi 7250). Through an interactive ParaView session using VNC server, the data set was loaded and rendered remotely. We decided to create streamlines for vorticity and represent three different classes (low, medium, and high) of its magnitude. Pressure values were represented by a gradient of a single color of the two slices. The vorticity was represented by a categorical (discrete) color map of three Hue values to show the classifications of vorticity values. Moreover, the vorticity color map was designed to be a colorblind safe map.

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Author Biography

I’m a postdoctoral fellow at TACC’s Scalable Visualization Technologies. Prior to TACC, I worked with the high-performance visualization group in Advanced Research Computing at Virginia Tech. I earned my Ph.D. in Computer Science from Virginia Tech, and I’m a faculty member in the Scientific Computing department at Ain Shams University in Egypt.

HPC-Bench: A Tool to Optimize HPC Benchmarking Workflow

HPC-Bench is a general purpose tool to optimize HPC benchmarking workflow to aid in the efficient evaluation of performance using multiple applications with only a “click of a button” on an HPC machine. HPC-Bench allows multiple applications written in different languages, multiple parallel versions, multiple numbers of processes/threads to be evaluated with a single “click of a button”. Performance results are put into a database, which is then queried for the desired performance data, and then the R statistical software package is used to generate the desired graphs and tables. The use of HPC-Bench is illustrated with complex applications that were run on the National Energy Research Scientific Computing Center’s (NERSC) Edison Cray XC30 HPC computer.

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Author Biography

Gianina Alina Negoita received the B.S. degree in physics and the M.S. degree in atomic physics and astrophysics from the Department of Physics at the University of Bucharest in Romania, in 2002 and 2004, respectively. From 2002 to 2005 she worked as a scientific researcher in the field of nuclear astrophysics at Horia Hulubei National Institute of Physics and Nuclear Engineering in Bucharest-Magurele, Romania studying the nuclear effects on neutrino emissivities from neutron stars. Gianina Alina Negoita also obtained an M.S. and a Ph.D. in nuclear physics from Iowa State University, in 2008 and 2010, respectively. She worked on ab-initio many-body calculations for a set of nuclei using the realistic nucleon-nucleon interaction, JISP16. Gianina Alina Negoita is currently working toward the Ph.D. degree in the Computer Science Department at Iowa State University. She obtained an M.S. in Computer Science from Iowa State University in Fall 2013. Her research interest is in the field of Parallel and High Performance Computing, doing performance evaluation for SHMEM (Shared Memory Routines) and MPI (Message Passing Interface) libraries, as well as machine learning and nuclear physics applications.

Comparison of Machine Learning Algorithms and Its Ensembles on Botnet Detection

A Botnet is a network of compromised devices that is controlled by malicious ‘botmaster’ in order to perform various tasks, such as executing DoS attack, sending SPAM and obtaining personal data etc. As botmasters generate network traffic while communicating with their bots, analyzing network traffic to detect Botnet traffic can be a promising feature of Intrusion Detection System(IDS). Although IDS has been applying various machine learning (ML) techniques, comparison of ML algorithms including their ensembles on Botnet detection has not been figured out yet. In this study, not only the three most popular classification ML algorithms – Naïve Bayes, Decision tree, and Neural network are evaluated, but also the ensemble methods known to strengthen ML algorithms are tested to see if they indeed provide enhanced predictions on Botnet detection. This evaluation is conducted with CTU- 13 public dataset on Spark, measuring running time of each ML and its f measure and MCC score.

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Author Biography

Songhui Ryu is a Master’s student with particular interests in big data analysis and machine learning. Working as a research assistant at research computing group at Purdue (RCAC), she has been working on system log analysis, network traffic analysis combined with machine learning technologies on clusters. She is pursuing a M.S. in Computer and Information Technology at Purdue University and holds a B.S. in Computer Science from Sungkyunkwan University, S. Korea.

High Performance Computing for Spiking Neuromorphic Network Training

Neuromorphic computing is a field in which neural networks are implemented in hardware to achieve intelligent computation with lower power and on a smaller footprint than traditional von Neumann architectures. One challenge for spiking neuromorphic computers, which implement spiking neural networks in hardware, is how to best train them. In this work, we utilize Oak Ridge National Laboratory’s Titan supercomputer to construct a spiking neuromorphic network for a particular neuromorphic hardware system (Dynamic Adaptive Neural Network Array or DANNA) to solve an obstacle avoidance, environment exploring robotic navigation task. We utilized a genetic algorithm for training our DANNA networks, in which each node on Titan either operated as a master or slave. Slave processes trained a subpopulation of networks and intermittently communicated their best result to one of the master processes, which communicated its best result to an overall “super-­master” process. We trained networks for this task on 18,000 nodes of Titan for 24 hours. The resulting network is the best network produced to date for all of our training approaches for the robotic navigation task. The network was trained in a simulation environment with obstacles and walls, but the resulting network was deployed on a physical robot in real environment. Utilizing Titan, we have successfully demonstrated that a network can be customized for a particular hardware platform, and that utilizing HPC resources can not only produce good networks faster, but it can also produce better networks than running on a single machine for weeks or months.

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Author Biography

Catherine D. Schuman (Katie) is a Liane Russell Early Career Fellow in the Computational Data Analytics group at Oak Ridge National Laboratory. Katie received her doctorate in computer science in 2015 from the University of Tennessee, where she completed her dissertation on the use of evolutionary algorithms to train spiking neural networks for neuromorphic systems. She is continuing her study of models and algorithms for neuromorphic computing as part of her fellowship at ORNL. Katie has co-­‐‑authored 20 publications in neuromorphic computing, and presented her work at fourteen conferences and workshops. Katie is also a joint faculty member at the University of Tennessee (UT), where she, along with four professors at UT, leads the TENNLab neuromorphic research team.

High Performance Computing in Large-Scale Traffic Engineering Problems

An important problem in transportation engineering is the traffic assignment problem (TAP), which seeks to determine traffic flows on road networks that satisfy some equilibrium conditions. Since solving a large-scale TAP using an optimization algorithm is often slow, High performance computing (HPC) provides the memory and power to speed up the computation, thus allowing more detailed analysis.

We studied the Frank-Wolfe algorithm (FW) commonly used to solve the static TAP, which assumes constant demands rates between origin-destination (O-D) pairs. The FW is an iterative descent method in which each iteration finds a search direction going toward a smaller objective function value at a best step length. Finding the search direction involves determining shortest-paths between all O-D pairs based on travel costs at the current iteration. This computation accounts for more than 95% of the overall execution time. Though there are some works that study parallel shortest-path algorithms, to the best of our knowledge, our work is the first to incorporate a parallel shortest- path algorithm into the FW applied to TAP.

We implemented the parallel FW on the Edison supercomputer at NERSC (nersc.gov). Our initial parallelization duplicated the network on 5 compute nodes, and equally divided the O-D pairs among 120 cores (24 cores per node). The 120 cores computed the shortest-paths for their assigned O-D pairs simultaneously. We tested this algorithm using the Chicago network, which had 12,982 nodes 39,018 links and 1,360,427 O-D pairs. The computation time was reduced by a factor of 25 compared to the sequential FW.

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Author Biography

Juliette Ugirumurera is a postdoctoral research fellow in Scalable Solvers Group of the Computational Research Division at the Lawrence Berkeley National Laboratory. She is developing parallel algorithms to solve large-scale traffic engineering problems. Juliette completed her PhD in Computer Science at the University of Texas at Dallas in 2016, where she modeled and designed algorithms to solve resource scheduling problems in Microgrid power systems. Her research interests include optimization, resource scheduling in complex networks, algorithm design, and Internet of things.

An Automatic Hardware Software Co-design for Exploring Sensitivity Analysis of Applications

Hardware-software co-design is increasingly important as we approach the Exascale era, particularly because of the tremendous increase in complexity, scale, and performance. Numerous solutions have been proposed to maximize the performance of the application using a combination of hardware and software optimization techniques, e.g., memory throttling and DVFS. However, we argue that none of these approaches are generic and effective unless we understand the impact of the hardware on an application’s expected performance combined with the impact of software optimizations. We explore this problem by analyzing the sensitivity of application performance to changes in hardware configurations. We also present analysis of how to improve application performance by changing hardware configuration, hence our work serves as a guideline for reconfigurable hardware. We base our analysis on automated hardware software co-design using the Aspen domain specific language. We believe that automated discovery of hardware and software characteristics can help modelers keep pace with architectural changes and the ever-increasing demand for performance with lower energy and resource consumption. We further use this automatic discovery of hardware and software characteristics and parameters to understand the impact they have on each other, and how we can use application behavior analysis to improve performance. We tested our approach on three diverse proxy applications — CoMD, Matrix Multiply and Jacobi— running on CPU-GPU based heterogeneous architecture. In future, we plan to explore our approach on other heterogeneous architectures including disaggregated systems.

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Author Biography

Mariam is a final-year Ph.D. student at the department of Computer Science, Virginia Tech. She is planning to graduate in early-Spring, 2018. Her research interest lies in exploring and implementing energy and performance models and methodologies for current and future Exascale architectures. She encompasses analytical, empirical and machine learning modeling techniques in conjunction with Aspen domain specific language for understanding the impact of performance and energy modeling on hardware software co-design techniques for current and future architectures. She explores the impact of improving performance using software as well as hardware configuration at runtime and beforehand. She also has experience in developing digital-signal-processing methods for embedded systems and models for routing and channel optimization for wireless networks. In future, she plans to investigate power- aware architectures for exascale systems and be involved with efforts that meet the goals set by DOE for power consumption by for HPC.

ACES-Cosim: A Framework to Simulate Advanced Electric Distribution Systems at Scale for Controller Architecture Research

Distributed Energy Resources (DERs), such as Photovoltaics (PV) and energy storage systems, have the potential to reduce the cost of electricity and the environmental impact of producing electricity. But DERs must be connected to the grid such that reliability is not impacted. High-fidelity simulation of the distribution power system, interacting DER’s, their controllers, control architectures and interactions with real hardware are required for a full understanding of these complex systems.The Advanced Computational Energy Systems (ACES)-Cosim, an agent-based modeling and co-simulation framework is targeted at addressing these problems.

ACES-Cosim hosts the connection and evolution in time of controllers, high-fidelity thermal and power models, power system simulators, and hardware using a powerful discrete event simulator paradigm. In pursuing high fidelity simulation and utilization of the ACES-Cosim framework to investigate real-
time distributed control architecture, the following challenges needed to be addressed: Interactive real-time visualization of the system running the simulation to monitor and debug controllers; Asynchronous execution of supervisory controllers and equipment models to make use of multiple cores on a High performance Computing (HPC) system node; Multi-node parallelism for large numbers of controllers and equipment to overcome the memory and processing bottlenecks of a single node; Multi-language support for controller and equipment models in Matlab, Python etc. to enable wider use of the framework by domain experts.

Remaining challenges include, augmenting the existing framework to study the control architectures under varying communication network conditions, and additionally scaling the framework to simulate thousands of controllers and devices.

Poster download

Author Biography

Deepthi Vaidhynathan received her M.S. degree in electrical engineering from the University of Colorado at Boulder in 2015. She works in the Computational science Center at NREL in the Complex system Simulation and optimization group. Her research interests include modeling and simulating for the transmission and distribution grid, software architecture for energy system integration research, and parallel performance engineering.

Co-Founder Women in HPC, EPCC at the University of Edinburgh

Toni Collis is an Applications Consultant in HPC Research and Industry, providing consultancy and project management on a range of academic and commercial projects at EPCC, the University of Edinburgh Supercomputing Centre.

Toni has a wide ranging interest in the use of HPC to improve the productivity of scientific research, in particular developing new HPC tools, improving the scalability of software and introducing new programming models to existing software. Toni is also a consultant for the Software Sustainability Institute and a member of the ARCHER team, providing ARCHER users with support and resources for using the UK national supercomputing service as effectively as possible. In 2013 Toni co-founded Women in HPC as part of her work with ARCHER. Women in HPC has now become an internationally recognised initiative, addressing the under-representation of women working in high performance computing.

Toni is Inclusivity Chair and a member of the Executive committee for the SC17 conference. Toni is also a member of the XSEDE Advisory Board and has contributed to the organisation and program of a number of conferences and workshops over the last five years.

President of Data Vortex Technologies

Carolyn Coke Reed Devany is the President of Data Vortex Technologies, an Austin, Texas-based HPC company featuring a proprietary network solution for HPC, Big Data Graph Analytics and Neuromorphic Computing. Carolyn works directly with federal and academic HPC customers, the tech investor community, and manages the company’s industry partnerships. During her 20 year tenure in the HPC community, she has noticed, and grown concerned by, the scarcity of women at the senior leadership level. Carolyn has been a member of the Women in HPC Advisory Council since SC15 and is passionate about addressing the lack of diversity in the broad HPC community.

Vice President and General Manager of the Technical Computing Initiative (TCI) in Intel’s Data Center Group

Trish Damkroger is Vice President and General Manager of the Technical Computing Initiative (TCI) in Intel’s Data Center Group. She leads Intel’s global Technical Computing business and is responsible for developing and executing Intel’s strategy, building customer relationships and defining a leading product portfolio for Technical Computing workloads, including emerging areas such as high performance analytics and artificial intelligence. This includes traditional HPC, workstations, processors and co-processors, and includes all aspects of solutions including industry leading compute, storage, network and software products. Ms. Damkroger has more than 27 years of technical and managerial roles both in the private sector and within the United States Department of Energy, most recently as the Associate Director of Computation (Acting) at Lawrence Livermore National Laboratory leading a 1,000 person group that is one of the world’s leading supercomputing and scientific experts. Since 2006, Ms. Damkroger has been a leader of the annual Supercomputing Conference series, the premier international meeting for high performance computing. She was the SC14 General Chair in New Orleans and has held many other committee positions. She was named one of HPCwire’s People to Watch in 2014. Ms. Damkroger has a master’s degree in electrical engineering from Stanford University.

Director of Visualization & Senior Research Scientist

Kelly Gaither is the Director of Visualization, a Senior Research Scientist, and the interim Director of Education and Outreach at the Texas Advanced Computing Center (TACC) at The University of Texas at Austin. Dr. Gaither leads the visualization activities while conducting research in scientific visualization, visual analytics and augmented/virtual reality. She received her doctoral degree in Computational Engineering from Mississippi State University in May, 2000, and received her masters and bachelors degree in Computer Science from Texas A&M University in 1992 and 1988 respectively. Gaither has over thirty refereed publications in fields ranging from Computatational Mechanics to Supercomputing Applications to Scientific Visualization. She is currently a co-PI and the director of Community Engagement and Enrichment and for Extreme Science and Engineering Discovery Environment (XSEDE2), a $120M project funded by the National Science Foundation. She has given a number of invited talks and keynotes. Over the past ten years, she has actively participated in conferences related to her field, specifically acting as general chair IEEE Visualization 2004 and general chair of XSEDE16.

Acting Lead of the User Engagement Group

Rebecca Hartman-Baker is the acting leader of the User Engagement Group at the National Energy Research Scientific Computing Center at Lawrence Berkeley National Laboratory. She is a computational scientist with expertise in the development of scalable parallel algorithms for the petascale and beyond. Her career has taken her to Oak Ridge National Laboratory, where she worked on the R&D100-award winning team developing MADNESS and as a scientific computing liaison in the Oak Ridge leadership computing facility; the Pawsey Supercomputing Centre in Australia, where she coached two teams to the Student Cluster Competition at the annual Supercomputing conference and led the decision-making process for determining the architecture of the petascale supercomputer; and NERSC, where she is responsible for NERSC’s engagement with the user community to increase user productivity via advocacy, support, training, and the provisioning of usable computing environments. Rebecca earned a PhD in Computer Science, with a certificate in Computational Science and Engineering, from the University of Illinois at Urbana-Champaign.

Research Architect

Adrian obtained a degree in Computer Science from The University of Edinburgh before going on to become one of the students in the first year of EPCC’s fledgling MSc in HPC. After completing the MSc he joined EPCC as an Application Consultant and has been here ever since.

Director, Hartree Centre, UK

Alison Kennedy is the Director of the STFC Hartree Centre, having joined in March 2016.

The Hartree Centre provides collaborative research, innovation and development services that accelerate the application of HPC, data science, analytics and cognitive techniques, working with both businesses and research partners to gain competitive advantage. Prior to joining Hartree, she worked in a variety of managerial and technical HPC roles at EPCC for more than 23 years.

CEO and Co-Founder XandMcMahon
As the President and CEO of McMahon Consulting and the CEO and co-founder of Xand McMahon, Kim brings a wealth of knowledge and experience to her customers. Being in HPC and high-end IT since 1999 with companies such as SGI, Cray, and LSI/NetApp in a range of roles including leading and executing the go-to-market strategy for business units, managing partner relationships, co-marketing, product management, and sales, Kim shapes the strategy and offerings for McMahon Consulting and Xand McMahon while also leading the team on project execution. Working with clients all over the world and in the multiple technologies used in HPC and HPC-like vertical markets, her experience easily translates across borders helping companies bring their products to market in the US – both new products or an expansion into a new territory.

Kim is on the Executive Board of Women in HPC, where she leads the marketing and messaging of the organization, is the Communications lead for the SC17 Inclusivity Committee, manages the social media for HPC Advisory Council, and volunteers with various foundations in the Colorado area to assist with their marketing activities. Kim is a graduate of the University of Northern Colorado with a Bachelor of Science in Accounting / Business Administration.

Lawrence Livermore National Laboratory

Kathryn Mohror is a computer scientist on the Scalability Team at the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory (LLNL) since 2010. Kathryn’s research on high-end computing systems is currently focused on scalable fault tolerant computing and I/O for extreme scale systems. Her other research interests include scalable performance analysis and tuning, parallel programming paradigms, and she leads the Tools Working Group for the MPI Forum. Kathryn received her Ph.D. in Computer Science in 2010, an M.S. in Computer Science in 2004, and a B.S. in Chemistry in 1999 from Portland State University (PSU) in Portland, OR.

Argonne National Laboratory

Misbah Mubarak is a postdoctoral researcher at Argonne National Laboratory. At Argonne, she is part of the data-intensive science group that is working to enable researchers make use of their big data in new scientific advances. . She is the recipient of U.S. Fulbright scholarship, ACM SIGSIM PADS PhD colloquium award and a finalist for Google Anita Borg scholarship. Misbah received her PhD and Masters in computer science from Rensselaer Polytechnic Institute (RPI) in 2015 and 2011 respectively. She also has experience working at CERN, Switzerland and Teradata Corporation.

Misbah has authored or co-authored over 25 papers in the area of performance modeling and analysis for High-Performance Computing. She has served as a peer reviewer for a number of journals including ACM Transactions on Modeling and Simulation, ACM Transactions on parallel computing and IEEE journal of computers. She has served as the technical program committee member of ACM SIGSIM PADS conference in 2016 and 2017, publicity chair for ACM SIGSIM PADS in 2017 and organizing committee member of the women in HPC workshop at Supercomputing (SC) 2016.

General Manager

Jessica Popp is the General Manger for the Infinite Memory Engine (IME) division at Data Direct Networks (DDN). Her division is responsible for the development and support of the IME Burst Buffer product for HPC. Prior to joining DDN, Jessica was the Director of Engineering for the High Performance Data Division at Intel, responsible for the development and support of the Lustre parallel file system. Jessica’s career, spanning more than 20 years has been focused on software development. She started as an application programmer in industry, moved to data warehousing before big data was even a ‘thing’, and then found herself in HPC ten years ago somewhat accidentally as she followed her passion for leading software teams. Having spent much of her career being the only, or one of a very few women on a team, she is excited to see and be a champion for the increased focus on diversity in engineering.

Biography

Cristin Merritt has focused her career in software adoption in new frontiers. First taking on SAP enterprise implementations in the US, UK, and Middle East and then in convincing accountants to tag up tax returns for the HMRC using a cloud tool. She now works in HPC public cloud adoption, working hand-in-hand with a client base focused on testing the boundaries of HPC and looking for new ways to exploit public cloud for fast, affordable usage. Cristin earned her B.A. in Classics from the University of Florida in 2001, enjoys crochet, and foolishly signs up and runs marathons every now and again.

Abstract: In defense of public cloud: Achieving on-demand accessibility in High Performance Computing (HPC) in single-user, ephemeral projects, through the Alces Gridware Project

Ensuring the end user has access to fast, flexible and collaborative High Performance Computing (HPC) is a chief concern of those who are in the race for producing results in the highly competitive fields of science and engineering. With the advent of public cloud the concept of time to acquisition has shortened dramatically, down to a matter of days if not hours depending on project size. Through the Open Source Alces Gridware Project we created Alces Flight, a product that provides a fully featured, scalable HPC environment for research and scientific computing. Our intent was to create a free tier, aimed at the single user, with hopes to yield results as to how an individual researcher would approach and consume on- demand HPC resource. In the past ten months leaders in commercial manufacturing, cancer treatment, genomics, UAV consulting, and research universities have worked with Alces to create use cases for HPC in the public cloud. Our initial results show:

• • Acquisition of public cloud over traditional HPC server time is startling quick, with a current average time of a day and a half, including overview training of the platform.
  • Ephemeral (temporary) workloads that are embarrassingly parallel work best with auto-scaling HPC clusters, in one project case saving 64% on operational costs.

Alces Flight Compute, Solo Community Edition, yields an 80% reduction in time spent tuning the application to the platform manually.

Biography

Marisol Monterrubio-Velasco studied Physics in the National Autonomous University of Mexico (UNAM). In her final project, She studied and characterized the fractal growth of the largest sub-aquatic cave systems in the world. She used the physical model of Limited Aggregation by Diffusion to simulate the growth processes. In 2007 she started her postgraduate studies at the Polytechnic University of Catalonia within the Research program in Computational and Applied Physics. She received her PhD from the Polytechnic University of Catalonia (Spain) in 2013 including a Cum Laude award for her research. From 2014 to 2016 she was a postdoctoral researcher at Geosciences center, UNAM. At present she has a postdoc fellowship in the Barcelona Supercomputing Center thanks to a Mexican council for Science and Technology. Her research interests focus on computational physics, complex networks, statistical analysis and numerical simulation applied to earthquakes.

Abstract: Earthquakes simulation by using the Fiber Bundle model and Machine learning techniques

Earthquakes are the result of rupture processes in the Earth’s crust produced by a sudden energy release of the long-term accumulated stresses. Although we have knowledge about the occurrence of certain major earthquakes, our observational span is too short to be able to draw strong (predictive) conclusions about when, where and how big the next earthquake will be. Computational physics offers alternative ways to study the rupture process in the Earth’s crust by generating synthetic seismic data using physical and statistical models. The Fiber Bundle model (FBM), which describes the complex rupture processes in heterogeneous materials in a wide range of phenomena, has shown the ability to generate data that depicts the main characteristics of real seismicity [Moreno et al,. 2001; Monterrubio et al., 2015]. In order to obtain statistical significance and an appropriate parametric study, a large number of simulations is required. High-performance computing (HPC) combined with Machine Learning (ML) techniques provide a good ground base to perform and improve the simulations, the data management process and data analysis. This study includes the analysis of the relationship between the initial parameters of the simulations and the resulting characteristics exhibited in the aftershock simulation as the magnitude-frequency relation [Gutenberg and Richter, 1954], temporal decay behavior [Utsu, 1995] and spatial distribution [King et al., 1994]. Pattern recognition techniques are used to identify patterns in different scenarios. Lastly, classification of seismic events is accomplished through unsupervised clustering methods.

Biography

Ruth Schöbel is a PhD student at Jülich Supercomputing Centre since one year. Together with the Technical University of Dresden, Germany, she is working in the field of parallel-in- time integration methods for partial differential equations. As a member of the German project ParaPhase she is developing space-time parallel adaptive algorithms for phase- field models on HPC architectures, wherein her personal focus is the innovative
parallelization in the temporal direction. She already holds a Masters degree in Mathematics from the RWTH Aachen, and is also trained as a mathematical-technical software developer by the Forschungszentrum Jülich. She is specialized in numerical mathematics and has developed a particular interest in semi-implicit time-stepping methods for differential equations.

Abstract: Parallel-in-Time Integration with PFASST

The efficient use of modern high performance computing systems for solving space-time- dependent differential equations has become one of the key challenges in computational science. Exploiting the exponentially growing number of processors using traditional techniques for spatial parallelism becomes problematic when, for example, for a fixed problem size communication costs begin to dominate or for increased spatial resolution more time-steps are necessary due to stability constraints. Parallel-in-time integration (“PinT”) methods have recently been shown to provide a promising way to extend these prevailing scaling limits.

One promising PinT algorithm, the “parallel full approximation scheme in space and time” (PFASST), is an iterative, multilevel strategy for parallelization in the temporal dimension. For our experiments, we develop a software module called dune-PFASST, a C++ implementation using the “Distributed and Unified Numerics Environment”, which is a framework for solving PDEs with grid-based methods. Operating with this software we will report on our experience using PFASST in time together with finite elements in space and show first results. This work is conducted within the German project “ParaPhase”, where the final goal is the development of a highly scalable space-time parallel adaptive algorithm for the simulation of phase-field models. The open-source software dune- PFASST also contains various flavors of spectral deferred correction methods and will be made available online soon.

Biography

Martina graduated 2010 in statistics at the University of Vienna. She then decided to do her Masters degree in Technical Mathematics at the University of Innsbruck where she received her Masters Degree in 2013. Her Master thesis was written in the field of numerical analysis, which fostered her interest in the development of numerical methods as well as their implementation.

An internship at Lawrence Livermore National Laboratory in the following summer introduced her to high performance computing. Since 2014, her PhD thesis is funded by the Vienna Scientific Cluster (VSC) school, which gave her the opportunity to work an various projects with the focus of implementing numerical methods on HPC hardware. In addition, Martina Prugger spend a year in New Orleans working with Prof. Kurganov on numerical methods and has an active collaboration with the high performance computing group at SIMULA in Oslo.

Abstract: Numerical methods and their implementation on HPC hardware

Performing a numerical simulation on a supercomputer requires both an efficient parallelization as well as a good numerical algorithm. In this work we consider both of these aspects in the context of a fluid dynamics code.

More specifically, we introduce a numerical second order method to solve the Euler equations of gas dynamics in two spatial dimensions. This approach does not rely on dimension splitting and is consequently able to better resolve the numerical solution.

Furthermore, we investigate the feasibility of the programming paradigm Unified Parallel C (UPC), (a partitioned global address space (PGAS) extension to C) from a code developing point of view. Due to the shared memory model of PGAS languages, parallelizing a code is easier compared to using MPI. However, it is not clear how ease of development can be reconciled with performance. We present a UPC implementation of a Godunov solver to represent a compute bound real live problem and compare various optimized stages of the parallelization to an MPI implementation of the same sequential code. Furthermore, we introduce a sparse matrix vector multiplication on highly unstructured data that is taken from a simulation of the human heart and is a memory bound problem.

Biography

Carla Osthoff is a researcher at National Laboratory for Scientific Computing (LNCC- Brazil), she received her B.S. in Electronics Engineering from PUC-RJ, a M.S. and a Ph.D. in Computer Science from COPPE / UFRJ. She have been working in high performance computing since 1985, first on parallel multiprocessor hardware projects, followed by distributed shared memory systems development. Currently, she works on High Performance Computing Research as a professor from National Laboratory of Scientific Computing Multidisciplinary Postgraduate Program and coordinates the National Center for High Performance Processing (CENAPAD) from LNCC. Currently topics of interest are distributed systems, high performance computing, parallel processing, programming models and scientific computing.

Abstract: K-mer frequency counting software based on a hybrid GPU cluster environment

Although metagenomics is a new area in science, in recent years there has been an explosion in computational methods applied to metagenome. The development of sequencing technology has exponentially increased the amount of data from sequencing files from genetic samples and consequently analysis complexity. Most of tools used to compress sequencing data employs k-mers algorithms, which collects all possible k length combinations from a data sequence. Due to their combinatorial nature, k-mers algorithms demands a lot of processing power. This work presents the development and performance analysis form a deterministic k-mer accounting algorithm for a GPGPU computer server based architecture, CFRK, which can be considered a low- cost, high-performance computing platform. After the validation tests, we demonstrate that CFRK is more efficient than k-mer state of the art algorithm
Jellyfish, based on multicore shared memory computing platform, for k values below 4. We also present the development from a CFRK extension for hybrid GPU clusters environments, MCFRK, based on MPI library, that improves CFRK performance and capacity to process larger files and presents better performance than Jellyfish for k-mer values most used for metagenome analysis.

Biography

Radita is a first year master’s student in Computer Science at University of Tartu, Estonia. She received her bachelor degree in Information System from Duta Wacana Christian University, Indonesia. She is currently taking High Performance Computing specialization and having interest in scalable web application.

Abstract: Parallel Cuckoo Hashing Implementation using Node JS Cluster Module

In recent years, Node.js server has gained increasing popularity as a web server due to its configuration simplicity and capability to handle high traffic web applications. A single instance of Node.js runs in a single thread but it is also capable of taking advantage of multi-core systems by creating child processes using Node JS Cluster module.

In this work we demonstrate this parallel capability of the Node JS Cluster module by building hash tables using Parallel Cuckoo Hashing algorithm. Hash table creation in web applications, so far, has been a common way to store data from the database query or from other sources. Hash table data structure enables easier and faster data access by the web application. Usually, Cuckoo hashing is used to resolve collision from hash table insertion by evicting conflicting values and moving them to other hash tables. It’s very easy to implement and quite efficient in practice.

Produced results from this implementation shows that a hash table that is built using Parallel Cuckoo Hashing can be built at a rate of around 0.28 – 1,64 times faster than its serial implementation. It depends on the size of data inserted. The bigger the data size, the more effective it gets. Its performance is also affected by number of cores on the system. The effective number of child processes that can be created follows the number of cores on the system.
Project Repository: https://github.com/raymerta/parallel-nodejs-benchmark

Biography

Pilar Gomez is a Research Fellow at the Universidad Autonoma de Barcelona (UAB) where she is doing a PhD in Computer Science with focus on Parallel I/O for High Performance Computing Systems. She has co-authored four full- reviewed technical papers in journals and conference proceedings. Since 2007, she is a part-time professor at the UAB and she has worked during 7 years as a Software Engineer for several companies.

Abstract: Cloud platform as Test-Bed System for analyzing the scientific parallel applications

Currently, the use of public cloud platforms as infrastructure has been gaining popularity in many scientific areas and HPC is no exception. Unlike on tradi- tional HPC platforms, on a virtual cluster, users are their own administrators, making it easy to change the I/O system configuration. We present a method- ology to use virtual HPC systems, deployed in a cloud platform, as a Test-Bed system for evaluating and detecting performance inefficiencies in the I/O sub- system, and for taking decisions about the configuration parameters that have influence on the performance of an application, without compromising the per- formance of the production HPC system. The parameters of our I/O behavior models PIOM-MP and PIOM-PX are applied to obtain the I/O kernel of the par- allel application. The I/O kernel is replicated by using the IOR benchmark and executed in virtual HPC clusters to evaluate the I/O time and the bandwidth in different I/O system configurations. To deploy the virtual I/O subsystem, we have developed a plug-in for the StarCluster tool, which allows us to deploy the PVFS2 parallel file system quickly and automatically. Our experimental valida- tion indicates that virtual HPC clusters are a quick and easy solution for system administrators, for analyzing the impact of the I/O system on the I/O kernels of the parallel applications and for taking performance decisions in a controlled environment.

Founder and Director, Women in HPC, EPCC at the University of Edinburgh

Toni Collis is an Applications Consultant in HPC Research and Industry, providing consultancy and project management on a range of academic and commercial projects at EPCC, the University of Edinburgh Supercomputing Centre.

Toni has a wide-ranging interest in the use of HPC to improve the productivity of scientific research, in particular developing new HPC tools, improving the scalability of software and introducing new programming models to existing software. Toni is also a consultant for the Software Sustainability Institute and a member of the ARCHER team, providing ARCHER users with support and resources for using the UK national supercomputing service as effectively as possible. In 2013 Toni co-founded Women in HPC (WHPC) as part of her work with ARCHER. WHPC has now become an internationally recognized initiative, addressing the under-representation of women working in high performance computing.

Toni is SC17 Inclusivity Chair and a member of the Executive committee for the conference. Toni is also a member of the XSEDE Advisory Board and has contributed to the organization and program of a number of conferences and workshops over the last five years including as an Executive Committee member of the EuroMPI 2016 conference and leading seven WHPC workshops around the world.

Acting Associate Director for Computation at Lawrence Livermore National Laboratory (LLNL), USA

Trish Damkroger is Acting Associate Director for Computation at Lawrence Livermore National Laboratory (LLNL), and leads the 1,000-employee workforce behind the Laboratory’s high performance computing efforts.  LLNL’s computing ecosystem includes high performance computers, scientific visualization facilities, high-performance storage systems, network connectivity, multiresolution data analysis, mathematical models, scalable numerical algorithms, computer applications, and necessary services to enable LLNL mission goals and scientific discovery through simulation.

Ms. Damkroger has more than 27 years of technical and management roles both in the private sector, as Remedy Corporation’s Area Vice President for Information Technology, and elsewhere within the Department of Energy, as Sandia National Laboratories’ Deputy Director for the Advanced and Exploratory Program.

Since 2006, Ms. Damkroger has been a leader of the annual Supercomputing Conference series. She was the SC14 General Chair in New Orleans and has held many other committee positions, including Infrastructure Chair, Exhibits Chair, Panels Chair, and Workshops Chair.

Principle Researcher, Microsoft, USA

Kathryn S. McKinley is a Principal Research at Microsoft. She was previously an Endowed Professor of Computer Science at The University of Texas at Austin. She is interested in creating systems that make programming easy and the resulting programs correct and efficient. She and her collaborators have produced several widely used tools: the DaCapo Java Benchmarks (30,000+ downloads), Hoard memory manager, TRIPS Compiler, MMTk memory management toolkit, and Immix garbage collector. Her awards include the ACM SIGPLAN Programming Languages Software Award and eleven best paper and test-of-time awards from ASPLOS, OOPSLA, ICS, SIGMETRICS, IEEE MICRO Top Picks (4), SIGPLAN Research Highlights, and CACM Research Highlights (2). She currently serves on the CRA and CRA-W Boards. Dr. McKinley was honored to testify to the House Science Committee (Feb. 14, 2013). She is an IEEE and ACM Fellow and has graduated 22 PhD students. She and Scotty Strahan, her husband of 31 years, have three sons.

Abstract

Teaching Data Centers to Share

Web services, from search to games to stock trading, impose strict service-level objectives (SLO) on tail latency that result in servers executing at low average utilization (10 to 45%); turning off simultaneous multithreading (SMT); and executing only a single service, wasting resources, money, and energy. We introduce principled borrowing, which controls SMT hardware resources. Latency sensitive requests execute in one SMT hardware context (lane). Batch workloads execute with mutual exclusion in a partner lane, but only when no request is executing. We show our approach effectively utilizes cores at 100% without compromising SLOs. This result is surprising.

Productive and Healthy Academic Relationships

Research is a social process. Participating in your broader community, finding collaborators, managing your students and advisor are important social skills that substantially impact your happiness, the quality of your research, and your career. This talk covers some practical ways to build good relationships and teams at your home institutions and how to meet new people to build your network..

Research Faculty, Center for Education Integrating Science, Mathematics and Computing (CEISMC) at the Georgia Institute of Technology

Lorna Rivera serves as a Research Scientist II in Program Evaluation at the Georgia Tech Center for Education Integrating Science, Mathematics and Computing (CEISMC). Her work focuses on the intersection of scientific content, pedagogy, and equity with the goal of being both methodologically innovative and socially responsible. Rivera has conducted evaluations primarily funded by the National Science Foundation’s Division of Advanced Cyberinfrastructure. This has led her to work with over 18 universities as well as multiple international high performance computing centers and organizations such as Compute Canada, EPCC, NCSA, PRACE, RIKEN, and XSEDE. Rivera received both her Bachelor of Science in Health Education and her Master of Science in Health Education and Behavior from the University of Florida. Prior to joining Georgia Tech, Rivera worked with various institutions, including the University of Illinois at Urbana-Champaign, March of Dimes, Shands HealthCare, and the University of Florida College of Medicine. Her research interests include the evaluation of innovative programs and their sustainability.

Director of the National Energy Research Scientific Computing (NERSC)

Dr. Sudip Dosanjh is Director of the National Energy Research Scientific Computing (NERSC) Center at Lawrence Berkeley National Laboratory. NERSC’s mission is to accelerate scientific discovery at the U.S. Department of Energy’s Office of Science through high performance computing and extreme data analysis. NERSC deploys leading-edge computational and data resources for over 4,500 users from a broad range of disciplines. NERSC will be partnering with computer companies to develop and deploy pre-exascale and exascale systems during the next decade.
Previously, Dr. Dosanjh headed extreme-scale computing at Sandia National Laboratories. He was co-director of the Los Alamos/Sandia Alliance for Computing at the Extreme-Scale from 2008-2012. He also served on the U.S. Department of Energy’s Exascale Initiative Steering Committee for several years.
Dr. Dosanjh had a key role in establishing co-design as a methodology for reaching exascale computing. He has numerous publications on exascale computing, co-design, computer architectures, massively parallel computing and computational science.
He earned his bachelor’s degree in engineering physics in 1982, his master’s degree (1984) and Ph.D. (1986) in mechanical engineering, all from the University of California, Berkeley..

Director of Visualization & Director of Education and Outreach, Texas Advanced Computing Center (TACC)

Kelly Gaither is the Director of Visualization, a Senior Research Scientist, and the interim Director of Education and Outreach at the Texas Advanced Computing Center (TACC) at The University of Texas at Austin. Dr. Gaither leads the visualization activities while conducting research in scientific visualization, visual analytics and augmented/virtual reality. She received her doctoral degree in Computational Engineering from Mississippi State University in May, 2000, and received her masters and bachelors degree in Computer Science from Texas A&M University in 1992 and 1988 respectively. Gaither has over thirty refereed publications in fields ranging from Computatational Mechanics to Supercomputing Applications to Scientific Visualization. She is currently a co-PI and the director of Community Engagement and Enrichment and for Extreme Science and Engineering Discovery Environment (XSEDE2), a $120M project funded by the National Science Foundation. She has given a number of invited talks and keynotes. Over the past ten years, she has actively participated in conferences related to her field, specifically acting as general chair IEEE Visualization 2004 and general chair of XSEDE16. .

Chief Analyst and Senior Director of Market Intelligence, Intel Data Center Group

Debra is the Chief Analyst and Senior Director of Market Intelligence for Intel’s Data Center Group. Debra’s nearly 30 year career in High Performance Computing started at IDC where she spent 17 years leading the company’s presence in high end computing in government, academia and industry. She was instrumental in driving science and technology policy initiatives in the US and abroad, highlighting the impact and importance of HPC as a fundamental economic and innovation driver. She led IDG’s initiatives in healthcare and life sciences, launching Bio-IT World magazine and Expo, the Life Sciences Venture Fund and a research advisory and consultancy.

Following IDC, Debra was VP of Strategy for IBM’s Deep Computing organization, leading such initiatives such as IBM’s Blue Gene program and the early hosted HPC solutions of Deep Computing on Demand. She ran strategy and Market Intelligence for IBM’s System and Technology Group business unit driving critical BI and analytic programs and new modeling methodologies.

Debra was CEO of Tabor Communications, expanding the scope of the company beyond HPCWire, launching a Research organization, and building out a digital delivery platform. Following Tabor, Debra was at Microsoft leading strategy and evangelism, launching its Technical Computing Executive Advisory Council and driving several high profile collaborations with key partners including the Gates Foundation, UN, DoD, and NetHope.

Since joining Intel, Debra has led the company’s efforts on multiple fronts, including expanding the use and adoption of high performance computing into new markets and communities and driving strategy and pathfinding for Intel’s Technical Computing Group. In her current role as Chief Analyst and Sr. Director of MI, she is responsible for leading the vision and technical infrastructure around developing a world class MI organization for DCG.

She is actively involved in STEM policy initiatives and in working with global organizations to advance economic development through access and use of leading edge technologies. Outside of Intel Debra is active in the community sitting on several boards. She is a devoted mom and an avid skier.

Chief Analyst and Senior Director of Market Intelligence, Intel Data Center Group

Debra is the Chief Analyst and Senior Director of Market Intelligence for Intel’s Data Center Group. Debra’s nearly 30 year career in High Performance Computing started at IDC where she spent 17 years leading the company’s presence in high end computing in government, academia and industry. She was instrumental in driving science and technology policy initiatives in the US and abroad, highlighting the impact and importance of HPC as a fundamental economic and innovation driver. She led IDG’s initiatives in healthcare and life sciences, launching Bio-IT World magazine and Expo, the Life Sciences Venture Fund and a research advisory and consultancy.

Following IDC, Debra was VP of Strategy for IBM’s Deep Computing organization, leading such initiatives such as IBM’s Blue Gene program and the early hosted HPC solutions of Deep Computing on Demand. She ran strategy and Market Intelligence for IBM’s System and Technology Group business unit driving critical BI and analytic programs and new modeling methodologies.

Debra was CEO of Tabor Communications, expanding the scope of the company beyond HPCWire, launching a Research organization, and building out a digital delivery platform. Following Tabor, Debra was at Microsoft leading strategy and evangelism, launching its Technical Computing Executive Advisory Council and driving several high profile collaborations with key partners including the Gates Foundation, UN, DoD, and NetHope.

Since joining Intel, Debra has led the company’s efforts on multiple fronts, including expanding the use and adoption of high performance computing into new markets and communities and driving strategy and pathfinding for Intel’s Technical Computing Group. In her current role as Chief Analyst and Sr. Director of MI, she is responsible for leading the vision and technical infrastructure around developing a world class MI organization for DCG.

She is actively involved in STEM policy initiatives and in working with global organizations to advance economic development through access and use of leading edge technologies. Outside of Intel Debra is active in the community sitting on several boards. She is a devoted mom and an avid skier.

President and CEO, McMahon Consulting

Kim McMahon is the President and CEO of McMahon Consulting, a full-service marketing firm specializing in the HPC and Enterprise Technical Computing space. She has nearly 20 years of experience with companies such as SGI, Cray, ADIC, LSI/NetApp, and Brocade as well as in the areas of compute, storage, networking, cloud, big data, and services. She has held a range of roles including leading and executing the go-to-market strategies for business units, managing partner relationships, co-marketing, product management, and sales.

Kim has worked with clients all over the world. This worldwide exposure has given her the experience to market US products outside of the country and to help foreign companies launch and market their products in the US. Kim is on the Advisory Board and leads the marketing and communications for Women in HPC, is the Communications lead for the SC16 Diversity Committee and the SC16 Student Cluster Competition Committee, manages the SC16 Twitter, and manages the social media for HPC Advisory Council. Kim is a graduate of the University of Northern Colorado with a Bachelor of Science in Accounting / Business Administration. Kim grew up and lives in Colorado and in her free time you will find her outdoors skiing, hiking, or walking the dogs.

Postdoctoral Appointee, Argonne National Laboratory

Misbah Mubarak is a postdoctoral researcher at Argonne National Laboratory. She is part of the data-intensive and HPC storage research group at Argonne, which is working to enable researchers make use of their big data in new scientific advances. Misbah has authored or co-authored over 20 papers in the area of performance modeling and analysis of HPC systems. She is the recipient of U.S. Fulbright scholarship, ACM SIGSIM PADS PhD colloquium award and a finalist for Google Anita Borg scholarship. Misbah received her PhD and Masters in computer science from Rensselaer Polytechnic Institute (RPI) in 2015 and 2011 respectively. She also has experience working at CERN, Switzerland and Teradata Corporation.

• Neelofer Banglawala: Bespoke bone modelling with VOX-FE
• Hongmei Chi: Particle Swarm Optimization for High-dimensional Stochastic Problems
• Sharda Dixit: Automated Empirical Tuning of Performance and Power Consumption using region (CPU, Memory, I/O) driven DVFS for HPC Scientific Workloads
• Lydia Duncan: Array Initialization Improvements in Chapel
• Wei P Feinstein: Accelerating protein functional annotation with Intel Xeon Phi coprocessors .
• Rosa Filgueira : dispel4py – A Python toolkit for enabling the automatic portability of scientific applications among HPC architectures
• Meghan Fisher: Simulating Volcanic Eruptions on Early Mars
• Maria Juliana Garzón Vargas: High performance embedded computing platform for emergency vehicle transportation
• Patricia Grubel: Performance Characterization of HPX- A Task-based Runtime System on the Xeon PhiTM Knights Landing (KNL)
• Hanlin He : SuperLU Pilot Libraries on KNL Machine
• Zahra Khatami: HPX Data Prefetching Iterator
• Jiajia Li: Model-driven Sparse CP Decomposition for High-Order Tensors
• Fang Liu: Building a Research Data Science Platform from Industrial Machines
• Oana Marin: Lossy Data Compression in a highly scalable Computational Fluid Dynamics code
• Bhavani S Nanjundiah: High Performing Big Data Analytics using Spectrum Scale
• Lena Oden: Towards efficient usage of heterogeneous memory architectures
• Oluwabamise T Oluwaseyi: HPC advancement to other fields
• Maria Andrea Pimiento Ojeda: Processing and Visualization in Embedded Architectures of High Performance Computing
• Caitlin Ross: Performance Analysis and Visualization of Dragonfly Network Simulations
• Louise Spellacy: Partial Inverses of Block Tridiagonal Non-Hermitian Matrices
• Sangeetha Banavathi Srinivasa: Smart Load Balancing of File Systems in HPC clusters
• Daria Tarasova: Algorithm Development for Cloud-Based Quantitative Histological Image Analysis Tool
• Jesmin Jahan Tithi: Cache-oblivious wavefront algorithms for dynamic programming problems: efficient scheduling with optimal cache performance and high parallelism
• Mariam Umar: An Application and Hardware Driven Co-design for Current and Future Architectures Using Domain Specific Language
• Bharti Wadhwa: An Object-based Data Storage Interface for Future HPC Storage Hierarchy
• Zhengkai Wu: Predictive Ring Path Planning via 3D GPU Graphical Simulation in Subtractive 3D Printing
• Hongjie Zheng: Large-scale Tsunami Run-up and Inundation Simulation Using an Explicit Moving Particle Simulation Solver Framework

Co-Founder, Women in HPC, EPCC at the University of Edinburgh

Toni Collis is an Applications Consultant in HPC Research and Industry, providing consultancy and project management on a range of academic and commercial projects at EPCC, the University of Edinburgh Supercomputing Centre.

Toni has a wide-ranging interest in the use of HPC to improve the productivity of scientific research, in particular developing new HPC tools, improving the scalability of software and introducing new programming models to existing software. Toni is also a consultant for the Software Sustainability Institute and a member of the ARCHER team, providing ARCHER users with support and resources for using the UK national supercomputing service as effectively as possible. In 2013 Toni co-founded Women in HPC (WHPC) as part of her work with ARCHER. WHPC has now become an internationally recognized initiative, addressing the under-representation of women working in high performance computing.

Toni is SC17 Inclusivity Chair and a member of the Executive committee for the conference. Toni is also a member of the XSEDE Advisory Board and has contributed to the organization and program of a number of conferences and workshops over the last five years including as an Executive Committee member of the EuroMPI 2016 conference and leading seven WHPC workshops around the world.

Director, Hartree Centre, UK

Alison Kennedy is the current Managing Director of PRACE and is Chair of the Board of Directors of the Partnership for Research Computing in Europe (PRACE). She joined the STFC Hartree Centre in the UK as Director in March 2016.

The Hartree Centre provides collaborative research, innovation and development services that accelerate the application of HPC, data science, analytics and cognitive techniques, working with both businesses and research partners to gain competitive advantage. Prior to joining Hartree, she worked in a variety of managerial and technical HPC roles at EPCC for more than 23 years.

I-STEM Senior Research Specialist, University of Illinois at Urbana-Champaign

Lorna Rivera serves as an I-STEM Senior Research Specialist working on a nationwide project funded by the National Science Foundation: Extreme Science and Engineering Discovery Environment (XSEDE). XSEDE seeks to help scientists and engineers around the world use their collection of integrated advanced digital resources and services to advance research in order to make us all healthier, safer, and better off.

Lorna Rivera received her Bachelor of Science in Health Education and her Master of Science in Health Education and Behavior from the University of Florida. In 2011, she was certified as a Health Education Specialist by the National Commission for Health Education Credentialing, Inc. Prior to joining I-STEM in Illinois, Lorna worked with various organizations, including the March of Dimes, Shands HealthCare, and the University of Florida College of Medicine. Her research interests include the evaluation of innovative programs and their sustainability, and health education and promotion programs.

CEO, McMahon Consulting

As the President and CEO of McMahon Consulting, a full-service marketing firm, I specialize in working with HPC and technology companies.

I’ve worked in HPC and technology since 1999 with SGI, Cray, ADIC, LSI / NetApp, and Brocade. I’ve held a range of roles – sales, product management, running business units, and marketing. I’ve had the opportunity to travel all over the world working with different types of customers and in multiple technologies such as compute, storage, networking, infrastructure, software, and services.

I am on the National Board of the National Association of Women Business owners, I volunteer my time and marketing skills for various foundations in the Colorado area, and I mentor many women in business on topics ranging from work/life balance to career growth.

I grew up and live in Colorado. In my free time, you will find me outdoors skiing, hiking or walking my dogs.

Senior Scientist & the Data Science and Technology Department Head, Lawrence Berkeley National Laboratory

Dr. Agarwal’s current research focuses on developing computational tools to enable scientists to more effectively organize and use their data to understand and mitigate climate change. She has worked on projects involving watershed understanding, tropical forests, soil carbon, carbon capture, cosmology, particle accelerators, and satellite data.

Dr. Agarwal earned her BS in Mechanical Engineering from Purdue University.  Her MS and PhD are from University of California, Santa Barbara in Computer Engineering. Dr. Agarwal’s career has taken her around the world including spending time consulting at the United Nations in Vienna, travel to India, travel to Japan and Taiwan, and a year working in Rennes, France on sabbatical at Inria. Dr. Agarwal is committed to increasing diversity of computing and is involved in organizing mentoring programs to help underrepresented groups succeed.

General Manager, High Performance Computing Platform Software

Figen joined Intel in November 2014 after 20+ years in software industry with experience in Technical Computing, Cloud and Data Science fields and is responsible for HPC Platform Software technologies for static and cloud workloads.

Most recently she was with Microsoft for 13 years in various software management and strategic planning roles that included Azure team and HPC team. Prior to Microsoft, Figen worked at McKinsey & Co consulting for Fortune 500 companies, at Motorola shipping software for mobile phones that earned her patents as a research scientist and in Justsystem Corp in Japan developing office suite of products for Japanese market. Her passion for intelligent systems is an extension of her PhD in Machine Learning and MSc in Expert Systems which she completed under a Fulbright scholarship.

Figen enjoys coaching women for career development, has been a Brownie Troop leader and has held a VP position in a non-profit organization in Japan to provide humanitarian aid to women all around the world impacted by the regional unrest.

PhD Candidate, University of Southampton

Poster available for download here.
I am a PhD student in the Faculty of Engineering and the Environment at University of Southampton since November 2015. I graduated with first class honours in Aerospace Engineering in 2015 from the same University.

My research topic is Advanced Internet of Things (IoT) for Engineering. My main interests are ubiquitous computing, indoor positioning and context-aware computing coupled to applications of IoT in engineering and science which may require large scale computing and data handling requirements

Abstract: Advanced Internet of Things for Engineering

In the last few decades Internet of Things (IoT) has developed at an exponential rate. A dynamic area that captivates the attention of both industry and academia, some consider Internet of Things the second technological revolution – the first one being the invention of the personal computer – and there are predictions claiming that by 2020 approximately 25 – 50 billion smart devices will be connected to the Internet.

Over the last few years the hardware capabilities have improved significantly, while their price and physical size highly decreased. This research is looking at next-generation IoT capabilities that are enabled by these advances.

We identify that a key enabler for Internet of Things is indoor positioning. Although a number of indoor localisation systems have been developed lately, there is still further work to be done to achieve a highly cost-effective, practical indoor positioning system. It is important that such systems can be deployed easily and used by anyone, and do not impose hardware or software restrictions on the user. The system would be an excellent ubiquitous computing platform that can be deployed at large scales to further enable context-aware applications. 

We have developed an indoor positioning system that is ubiquitous, has the capability to perform auto-calibration and the tracked devices do not have to be connected to a WiFi infrastructure. Further work will look at deploying the system across our University campus with the aim of performing advanced analytics and providing underpinning infrastructure for future research projects across our estate. It is likely that large amounts of data will be collected. This will be combined with other available data sources and analysed using high performance computing.

System Engineer at Callao’s University and Computer Science Master at Pontificia Universidad Católica del Peru

Poster available for download here.
I have been working with Linux related technologies during the last seven years. Enthusiastic involved in Linux projects such as GNOME (Member of the GNOME Foundation) and FEDORA (FEDORA Peru Ambassador). Thanks to these projects I was able to travel for more than twelve countries and I also have been Linux Administrator and IT Linux Specialist in companies such as GMD and IBM. Among academic life experiences, I lectured in universities like PUCP (Assistant’s Professor), USIL (Professor) and UNI (Professor) in courses that let me spread the Linux knowledge such as Operative System, Networking, Security and Linux courses. Recently, I have involved in HPC researches and I belong to the HPC group at CTIC-UNI. Parallel computing and heterogeneous parallel programming are now my research topics.

Abstract:

The starting point of this HPC experiment is by the use of a commodity HPC cluster. But, instead of using thousands servers that are work together for solving a single problem, we decided to use an educational system, the Cluster Cruz II, on which to install and configure Hadoop and MapReduce. This tool is useful in its low price, portability and flexibility, also has the key features such as the physical manipulation of SD card to support a lot of variations and changes.

We have finally a success to install the needed software when all the node of the cluster were with single model of Raspberry Pi 2 model B. The Raspbian OS (Jessie) was installed on the 4 nodes, and all the packages were installed without any compatibility issues. When we had the cluster architecture in which a Raspberry Pi 1 as the master node and all the other slaves were of Raspberry Pi 2, we have some failures to install software. The SD cards in use were of 32 GB and it does not matter even if not all of them are the same in brand or type.

During the experience, Linux has played an important role here during the formatting and labelling part. Before installing and configuring Hadoop 1.2.1 with MapReduce, we tested MPI by calculating the value of PI and NFS(service to share files throughout the cluster) installation. The next challenge accomplished was the installation of Java (requirement to install Hadoop), the open version was 8 in this experiment and then constructing the hierarchy of files to install Hadoop. After the configuration of the xml files, the configuration of the environments, you must learn the Hadoop commands (specially to manage inputs and output files) and Java libraries to run parallel program, to success. Next step will be Spark on Raspberry Pi.

This experiment was based in the book of Andrew K. Dennis: “Raspberry Pi Super Cluster”.

PhD Candidate, University of Edinburgh

Poster available for download here.
I did my undergraduate degree in physics at Grinnell College and many years later pursued an MSc in HPC from the University of Edinburgh. In the meantime, I’ve worked as a software engineer for biotech, geophysical and financial companies. I am currently part of the CDT in Pervasive Parallelism(link is external)researching performance portable solutions for room acoustics simulations.

Abstract: Performance, Portability and Productivity for Room Acoustics Codes

Currently there are a wide-range of methods available for parallelising code on different architectures, however these strategies are becoming more complex and less portable. Meanwhile rewriting and re-tuning code is a time-consuming task. OpenCL solves some of these problems, however the performance is not portable and the framework is very low-level for non-experts.

Parallel abstraction layers offer one possibility of de-coupling the need for parallel programming expertise from simulation modelling. A wide range of these types of solutions exist (including skeletons, code generators and low-level libraries), however many of them are still in early stages of developments or have been tested primarily on simple benchmarks. There remains no straightforward path between real world HPC applications and higher level abstraction frameworks for the purposes of writing simplified, performant, portable code.

This gap could be bridged by determining the limitations of current methods and adding new functionality and data abstractions with real simulation codes in mind. In the first instance, this will involve a case study for stencil applications, in particular room acoustics simulations developed by the NeSS project. These room acoustics models use a finite difference time domain discretisation method to simulate the behaviour of sound waves from different sources in a room. Firstly for these room acoustics codes, performance, optimisations and alternative data abstractions have been investigated across different platforms to determine any portability, performance portability and abstraction issues. These results will then be compared with more advanced room simulations to see if similar or new problems occur. Finally, attempts will be made to implement the room acoustics benchmarks in existing higher level frameworks. 

From this initial study, the intention is to ascertain if and where current parallel frameworks need more functionality for room acoustics simulations and further the development of parallelisable stencil abstractions able to fit a wider range of physical codes.