SC19 March Need to Know: Paper Submissions Open, Apply to WINS; Start Planning Your Awards Nominations; Workshop Submissions Review in Progress; Volunteers Explore Colorado Convention Center

Spring is almost here, and SC19 is blooming with submission and nomination opportunities, upcoming deadlines, and dedicated volunteer activity.   Papers, Papers, Papers! We know how eagerly everyone awaits the Papers submission window each year. You’ll be happy to know that window opened on March 1, which gives you just about a month before the

SC19 February Need to Know: Big Tech Program Submissions Open, Keep Up with Tech Program Enhancements, Become a Student Volunteer, Apply for the Student Cluster Competition

Welcome once more to those of you who read the January blog update and warm greetings to our new readers. As the path to SC19 unfolds, we hope more attendees will turn to this monthly summary for information about important dates and behind-the-scenes snapshots. If you’re new and want to catch up on past blog

Research Poster Submissions

How to Submit Overview Preparing Your Submission Where to Submit Reproducibility Initiative Review Criteria Conflict of Interest Plagiarism Upon Acceptance Registration Finalizing Accepted Research Posters Proceedings On-site Schedule and Location Infrastructure Posters Reception Awards How to Submit Overview SC’s Research Posters program provides a venue for researchers in industry, academia (including students), and government to

Newsletter

View the contents of SC19 Newsletters here. Newsletters contain news, articles from the blog, updates, and more. The Newsletter is delivered on the second Thursday of each month. Sign up and stay in the know! Read the SC19 Blog Visit the SC18 Newsletter Archive       December 12, 2019 Issue   SC News: HPC

Paper Submissions

How to Submit Overview Preparing Your Submission Where to Submit Reproducibility Initiative Review Criteria Review, Response, Revision Conflict of Interest Plagiarism Upon Acceptance Registration Finalizing Accepted Papers Proceedings On-site Schedule and Location Infrastructure Awards How to Submit Overview The SC Papers program is the leading venue for presenting high-quality original research, groundbreaking ideas, and compelling

Panel Submissions

How to Submit Overview Preparing Your Submission Where to Submit Review Criteria Conflict of Interest Plagiarism Upon Acceptance Registration Finalizing Accepted Panels Proceedings On-site Schedule and Location Infrastructure How to Submit Overview Panels create an opportunity for the community to engage in discussion on current HPC challenges and solutions. The goal of the Panels program

Student Cluster Competition

The Student Cluster Competition (SCC) was developed in 2007 to provide an immersive high performance computing experience to undergraduate and high school students. With sponsorship from hardware and software vendor partners, student teams design and build small clusters, learn scientific applications, apply optimization techniques for their chosen architectures, and compete in a non-stop, 48-hour challenge

Workshop Submissions

How to Submit Overview Preparing Your Submission Reproducibility Initiative Review Criteria Conflict of Interest Informational Webinars Upon Acceptance Registration Finalizing Accepted Workshops Collection and Review of Workshop Papers Proceedings Plagiarism On-site Schedule and Location Food and Coffee Breaks Infrastructure   How to Submit Overview SC presents full- and half-day workshops with the goal of expanding

Brian Skjerven

Brian Skjerven Pawsey Supercomputing Center Biography Brian Skjerven is a Supercomputing Application Specialist at the Pawsey Supercomputing Centre in Perth, Australia. His role involves supporting researchers across Australia in using Pawsey HPC facilities. He is particularly focused on enabling scientific workflows that incorporate Cloud

Adrian Jackson

Adrian Jackson University of Edinburgh Biography Adrian Jackson is a Research Architect at EPCC where he works on enabling computational simulation on very large parallel computers and novel hardware for research computing. He has recently led the architecture design for the European funded NEXTGenIO, creating an innovative new hardware and

Holger Brunst

Holger Brunst Technical University Dresden Biography Dr Holger Brunst is a Senior Research Fellow at the Center for Information Services and High Performance Computing (ZIH) of Technische Universität Dresden. He is a specialist in the field of performance analysis and regularly teaches software tuning classes. Prior to his position as a perf

Line Pouchard

Line Pouchard Brookhaven National Laboratory Biography Dr. Line Pouchard is a computational scientist who joined the Center for Data-Driven Discovery in the Computational Science Initiative at Brookhaven National Laboratory as a senior researcher in January 2017. She leads multidisciplinary efforts improving scientific data discovery, data management, and curation in scientific domains includ

Michael O. Lam

Michael O. Lam James Madison University Lawrence Livermore National Laboratory Biography Michael O. Lam is an Assistant Professor in the Computer Science Department at James Madison University in Harrisonburg, Virginia. He received his Ph.D. in Computer Science from the University of Maryland, College Park, and has conducted research at Law

Adrian Jackson

Adrian Jackson University of Edinburgh Biography Adrian Jackson is a Research Architect at EPCC where he works on enabling computational simulation on very large parallel computers and novel hardware for research computing. He has recently led the architecture design for the European funded NEXTGenIO, creating an innovative new hardware and

Shawn T. Brown

Shawn T. Brown McGill University Presentations Workshop Comparing Perturbation Models for Evaluating Stability of Post-Processing Pipelines in Neuroimaging Exascale Reproducibility Scalable Computing W

Juliana Freire

Juliana Freire New York University Biography Juliana Freire is a Professor at the Department of Computer Science and Engineering at New York University. She also holds an appointment in the Courant Institute for Mathematical Science and is a faculty member at the NYU Center of Data Science. Her research interests are in large-scale data analysis, visualization, and provenance management. An

Peter Coveney

Peter Coveney University College London Biography Prof Peter V. Coveney holds a chair in Physical Chemistry, is an Honorary Professor in Computer Science at University College London (UCL), a Professor in Applied High Performance Computing at the University of Amsterdam (UvA), and Professor Adjunct at Yale University School of Medicine (USA). He is Director of the Centre for Computational Sc

Ji Xue

Ji Xue College of William & Mary Presentations Paper SSD Failures in the Field: Symptoms, Causes, and Prediction Models Best Practices Energy Exascale Machine Learning Memory Modelling Networks Performance Power Reliability Reproducibility TP

Dylan Chapp

Dylan Chapp University of Delaware University of Tennessee Biography Dylan Chapp is a Research Associate advised by Dr. Michela Taufer at the Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville and a Ph.D. Student at the University of Delaware. Chapp earned his MS in Computer Science in 2017 and BS in Mathematics in 2014, both from the Univers

Torsten Hoefler

Torsten Hoefler ETH Zurich Biography Torsten is an Associate Professor of Computer Science at ETH Zürich, Switzerland. Before joining ETH, he led the performance modeling and simulation efforts of parallel petascale applications for the NSF-funded Blue Waters project at NCSA/UIUC. He is also a key member of the Message Passing Interface (MP

Rebecca Hartman-Baker

Rebecca Hartman-Baker Lawrence Berkeley National Laboratory Biography Rebecca Hartman-Baker leads 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

Rebecca Hartman-Baker

Rebecca Hartman-Baker Lawrence Berkeley National Laboratory Biography Rebecca Hartman-Baker leads 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

Tristan Glatard

Tristan Glatard Concordia University Presentations Workshop A Performance Comparison of Dask and Apache Spark for Data-Intensive Neuroimaging Pipelines Extreme Scale Computing Scalable Computing Scientific Workflows W Workshop Comparing Perturbation Models for Evaluating Stability of Post-Processing Pipelines in Neuroimaging Exascale Reproducibility Scalable Computing W

Gregory Kiar

Gregory Kiar McGill University Presentations Workshop Comparing Perturbation Models for Evaluating Stability of Post-Processing Pipelines in Neuroimaging Exascale Reproducibility Scalable Computing W

Ian Briggs

Ian Briggs University of Utah Biography Ian is a full time research associate at the University of Utah. His interests include floating point error estimation, mixed precision floating point code generation, race detection, compiler design, verification, assembly analysis, and additive manufacturing. Ian received his masters in computer scie

Neil Chue Hong

Neil Chue Hong University of Edinburgh Software Sustainability Institute Biography Neil is the founding Director of the Software Sustainability Institute, representing the Institute and UK researchers at a national and international level. His current research is in barriers and incentives in research software ecosystems and the role of sof

Michael Bentley

Michael Bentley University of Utah Biography Michael Bentley is a Ph.D Student in Computer Science at the University of Utah. He is advised by Professors Ganesh Gopalakrishnan and Tucker Hermans and works in collaboration with the Lawrence Livermore National Laboratory. Michael has focused his research on floating-point reproducibility of

Torsten Hoefler

Torsten Hoefler ETH Zurich Biography Torsten is an Associate Professor of Computer Science at ETH Zürich, Switzerland. Before joining ETH, he led the performance modeling and simulation efforts of parallel petascale applications for the NSF-funded Blue Waters project at NCSA/UIUC. He is also a key member of the Message Passing Interface (MP

Andrew Younge

Andrew Younge Sandia National Laboratories Biography Andrew J. Younge is a Senior Member of Technical Staff in the Scalable System Software department at Sandia National Laboratories. He currently serves as the Lead PI for the Supercontainers project under the DOE Exascale Computing Project and is a key contributor to the Astra system, the

Mark Gray

Mark Gray Pawsey Supercomputing Center Biography Mark brings a strong research and data management background to his role of managing Nimbus, the research cloud at Pawsey Supercomputing Centre. This includes management of the service, project allocations, training, procurement and technical oversight of the team at Pawsey operating the syst

Sudharshan Vazhkudai

Sudharshan Vazhkudai Oak Ridge National Laboratory Presentations Paper End-to-End I/O Portfolio for the Summit Supercomputing Ecosystem Architectures Data Analytics Data Management I/O Monitoring TP Workshop Applying Machine Learning to Understand the Write Performance of Large-Scale Parallel Filesystems Big Data Data Analytics Data Management Storage W Chair of Sessions Pa

Richard S. Canon

Richard S. Canon Lawrence Berkeley National Laboratory Lawrence Berkeley National Laboratory Biography Shane Canon is a Senior Engineer at Lawrence Berkeley Lab where he works in the NERSC Supercomputing Facility. Over Shane’s 20 year career, he has focused on enabling scientists to conduct breakthrough science using large-scale systems i

Howard Bushouse

Howard Bushouse Space Telescope Science Institute Presentations Workshop Panel Discussion Exascale Reproducibility Scalable Computing W Workshop Reproducibility and Provenance of James Webb Space Telescope Data Products Exascale Reproducibility Scalable Computing W

Michael Mascagni

Michael Mascagni Florida State University National Institute of Standards and Technology (NIST) Biography Michael Mascagni is a professor of Computer Science, Mathematics, and Scientific Computing at FSU and a Faculty Appointee at NIST. Prof. Mascagni’s expertise is in numerical and scientific computing, especially in aspects of stochastic

Olivier Iffrig

Olivier Iffrig European Centre for Medium-Range Weather Forecasts Presentations Paper An Early Evaluation of Intel’s Optane DC Persistent Memory Module and Its Impact on High-Performance Scientific Applications Best Practices Energy Exascale Machine Learning Memory Modelling Networks Performance Power Reliability Reproducibility TP

Tapasya Patki

Tapasya Patki Lawrence Livermore National Laboratory Biography Tapasya Patki is a Computer Scientist at the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory and the PI for the ECP Power Steering project. Her current research involves the design and implementation of Exascale operating systems and next-generat

Ignacio Laguna

Ignacio Laguna Lawrence Livermore National Laboratory Lawrence Livermore National Laboratory Biography Ignacio Laguna is a Computer Scientist at the Center for Applied Scientific Computing (CASC) at the Lawrence Livermore National Laboratory (LLNL), California. His main area of research is programing models and systems for high-performance

Richard S. Canon

Richard S. Canon Lawrence Berkeley National Laboratory Lawrence Berkeley National Laboratory Biography Shane Canon is a Senior Engineer at Lawrence Berkeley Lab where he works in the NERSC Supercomputing Facility. Over Shane’s 20 year career, he has focused on enabling scientists to conduct breakthrough science using large-scale systems i

Fabienne Jézéquel

Fabienne Jézéquel Sorbonne University Biography Fabienne Jézéquel has been Associate Professor in Computer Science in Panthéon-Assas University in Paris, France, since 1997. She leads the PEQUAN (PErformance and QUality of Algorithms for Numerical applications) team in the Computer Science Laboratory LIP6 of Sorbonne University in Paris, Fra

Antonino Bonanni

Antonino Bonanni European Centre for Medium-Range Weather Forecasts Presentations Paper An Early Evaluation of Intel’s Optane DC Persistent Memory Module and Its Impact on High-Performance Scientific Applications Best Practices Energy Exascale Machine Learning Memory Modelling Networks Performance Power Reliability Reproducibility TP

Thomas Ludwig

Thomas Ludwig German Climate Computing Center Presentations Workshop Panel Discussion Exascale Reproducibility Scalable Computing W

Michela Taufer

Michela Taufer University of Tennessee Biography Michela Taufer holds the Jack Dongarra Professorship in the Department of Electrical Engineering and Computer Science at the University of Tennessee Knoxville. She earned her undergraduate degree in Computer Engineering from the University of Padova (Italy) and her PhD in Computer Science from

Massimiliano Culpo

Massimiliano Culpo Sylabs Inc Biography Massimiliano Culpo is a Software Developer at Sylabs. His work is mainly related to the automation of software deployment on HPC clusters and to the reproducibility of the software environments provided to researchers. He has been a core developer of Spack since July 2015. Before being at Sylabs he wor

Howard Bushouse

Howard Bushouse Space Telescope Science Institute Presentations Workshop Panel Discussion Exascale Reproducibility Scalable Computing W Workshop Reproducibility and Provenance of James Webb Space Telescope Data Products Exascale Reproducibility Scalable Computing W

Michela Taufer

Michela Taufer University of Tennessee Biography Michela Taufer holds the Jack Dongarra Professorship in the Department of Electrical Engineering and Computer Science at the University of Tennessee Knoxville. She earned her undergraduate degree in Computer Engineering from the University of Padova (Italy) and her PhD in Computer Science from

Roman Iakymchuk

Roman Iakymchuk Sorbonne University Biography Roman Iakymchuk is a researcher at Sorbonne University. He obtained a Dr.rer.nat. (equiv. to PhD) in computer science from the RWTH Aachen University. During his PhD, he did an internship at the National Institute of Informatics, Tokyo, Japan. Between 2012 and 2015, Roman was a post-doctoral rese

Toshiyuki Imamura

Toshiyuki Imamura RIKEN Center for Computational Science (R-CCS) Biography Toshiyuki Imamura is currently a team leader of Large-scale Parallel Numerical Computing Technology at the Center for Computational Science, RIKEN. He received his Diploma (M.Sc.) and Doctorate (Ph.D.) in applied systems and sciences in 1993 and 2000, respectively, bo

Massimiliano Culpo

Massimiliano Culpo Sylabs Inc Biography Massimiliano Culpo is a Software Developer at Sylabs. His work is mainly related to the automation of software deployment on HPC clusters and to the reproducibility of the software environments provided to researchers. He has been a core developer of Spack since July 2015. Before being at Sylabs he wor

Ganesh Gopalakrishnan

Ganesh Gopalakrishnan University of Utah Biography Ganesh L. Gopalakrishnan, Professor of Computer Science, School of Computing, University of Utah, directs Graduate Studies and the Center for Parallel Computing. His research covers HPC program dependability, including data race checking for OpenMP/GPU, HPC system resilience, rigorous floati

Kento Sato

Kento Sato RIKEN Center for Computational Science (R-CCS) Biography Kento Sato is the team leader of High Performance Big Data Research Team at RIKEN Center for Computational Science. His research area is distributed systems and parallel computing, particularly in High Performance Computing (HPC). Major focuses of his research are applicatio

Allison Baker

Allison Baker National Center for Atmospheric Research (NCAR) Biography Allison Baker is a Project Scientist III at the National Center for Atmospheric Research (NCAR). Her research interests include high-performance computing, performance analysis, iterative linear solvers, Earth System models, data compression, and verification techniques.

Robert W. Robey

Robert W. Robey Los Alamos National Laboratory Presentations Workshop Fast, Good, and Repeatable: Summations, Vectorization, and Reproducibility Exascale Reproducibility Scalable Computing W

Tanzima Z. Islam

Tanzima Z. Islam Western Washington University Biography Tanzima Islam is an assistant professor at Western Washington University (WWU). Before joining WWU, Dr. Islam earned her Ph.D. in Computer Engineering from Purdue University and was a postdoctoral scholar at Lawrence Livermore National Laboratory. Broadly, Dr. Islam’s research interest

Pierre Rioux

Pierre Rioux McGill University Presentations Workshop Comparing Perturbation Models for Evaluating Stability of Post-Processing Pipelines in Neuroimaging Exascale Reproducibility Scalable Computing W

Alan C. Evans

Alan C. Evans McGill University Presentations Workshop Comparing Perturbation Models for Evaluating Stability of Post-Processing Pipelines in Neuroimaging Exascale Reproducibility Scalable Computing W

Eric Petit

Eric Petit Intel Corporation Presentations Workshop Comparing Perturbation Models for Evaluating Stability of Post-Processing Pipelines in Neuroimaging Exascale Reproducibility Scalable Computing W

Tanzima Z. Islam

Tanzima Z. Islam Western Washington University Biography Tanzima Islam is an assistant professor at Western Washington University (WWU). Before joining WWU, Dr. Islam earned her Ph.D. in Computer Engineering from Purdue University and was a postdoctoral scholar at Lawrence Livermore National Laboratory. Broadly, Dr. Islam’s research interest

Jacob Alter

Jacob Alter College of William & Mary Presentations Paper SSD Failures in the Field: Symptoms, Causes, and Prediction Models Best Practices Energy Exascale Machine Learning Memory Modelling Networks Performance Power Reliability Reproducibility TP

Michael Mascagni

Michael Mascagni Florida State University National Institute of Standards and Technology (NIST) Biography Michael Mascagni is a professor of Computer Science, Mathematics, and Scientific Computing at FSU and a Faculty Appointee at NIST. Prof. Mascagni’s expertise is in numerical and scientific computing, especially in aspects of stochastic

Michèle Weiland

Michèle Weiland Edinburgh Parallel Computing Centre Biography Dr Michèle Weiland is a Senior Research Fellow at EPCC and leads the H2020 FET-HPC NEXTGenIO project, as well as lead EPCC’s technical involvement in the ASiMoV Strategic Prosperity Partnership. Prior to this, she coordinated the FP7 project Adept, which investigated power and ene

Evgenia Smirni

Evgenia Smirni College of William & Mary Presentations Paper SSD Failures in the Field: Symptoms, Causes, and Prediction Models Best Practices Energy Exascale Machine Learning Memory Modelling Networks Performance Power Reliability Reproducibility TP

Todd Gamblin

Todd Gamblin Lawrence Livermore National Laboratory Biography 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

Torsten Hoefler

Torsten Hoefler ETH Zurich Biography Torsten is an Associate Professor of Computer Science at ETH Zürich, Switzerland. Before joining ETH, he led the performance modeling and simulation efforts of parallel petascale applications for the NSF-funded Blue Waters project at NCSA/UIUC. He is also a key member of the Message Passing Interface (MP

Alexis Ayala

Alexis Ayala Western Washington University Presentations Workshop Toward a Programmable Analysis and Visualization Framework for Interactive Performance Analytics Performance Programming Systems Visualization W Paper Performance Optimality or Reproducibility: That Is the Question Best Practices Energy Exascale Machine Learning Memory Modelling Networks Performance Power Reliability Rep

David H. Bailey

David H. Bailey Lawrence Berkeley National Laboratory University of California, Davis Presentations Workshop Reproducibility and Variable Precision Computing Exascale Reproducibility Scalable Computing W

Tiago Quintino

Tiago Quintino European Centre for Medium-Range Weather Forecasts Biography Dr Tiago Quintino is a Senior Analyst and Team Leader for Development of Production Services at ECMWF. He and his team develop high-throughput specialist software that supports ECMWF’s operational meteorological forecast model, systems for acquisition of incoming ob

Neil Chue Hong

Neil Chue Hong University of Edinburgh Software Sustainability Institute Biography Neil is the founding Director of the Software Sustainability Institute, representing the Institute and UK researchers at a national and international level. His current research is in barriers and incentives in research software ecosystems and the role of sof

Michael O. Lam

Michael O. Lam James Madison University Lawrence Livermore National Laboratory Biography Michael O. Lam is an Assistant Professor in the Computer Science Department at James Madison University in Harrisonburg, Virginia. He received his Ph.D. in Computer Science from the University of Maryland, College Park, and has conducted research at Law

Walid Keyrouz

Walid Keyrouz National Institute of Standards and Technology (NIST) Biography Walid Keyrouz is a Computer Scientist in the Software and Systems Group of the Information Technology Laboratory at the National Institute of Standards and Technology. Dr. Keyrouz received his MS and PhD from Carnegie Mellon University. His first involvement with HPC was in his masters thesis which analyzed the use

Simon Smart

Simon Smart European Centre for Medium-Range Weather Forecasts Biography Dr. Simon Smart is a Senior Analyst at ECMWF, and works on the large-scale data handling and storage systems for meteorological data. This work particularly involves the scalability aspects of data handling in large meteorological workflows taking into account the upcom

Jayaraman J. Thiagarajan

Jayaraman J. Thiagarajan Lawrence Livermore National Laboratory Biography Jayaraman J. Thiagarajan received the Ph.D. degree in electrical engineering from Arizona State University, Tempe, AZ, USA, in 2013. He is currently a Computer Scientist with the Center for Applied Scientific Computing, Lawrence Livermore Natio

Mark Parsons

Mark Parsons Edinburgh Parallel Computing Centre Biography Professor Mark Parsons is the Director of EPCC and holds a Personal Chair in High Performance Computing at the University of Edinburgh. His is also the Associate Dean for e-Research at the University. He has extensive experience and expertise in high-performance and data intensive co

Daichi Mukunoki

Daichi Mukunoki RIKEN Center for Computational Science (R-CCS) Biography Daichi Mukunoki is a research scientist at RIKEN Center for Computational Science (R-CCS) (Japan). He received his Ph.D. degree in computer science in 2013 from University of Tsukuba. He was a research fellow of the Japan Society for the Promotion of Science in 2013-201

Andy Dubois

Andy Dubois Los Alamos National Laboratory Presentations Workshop Fast, Good, and Repeatable: Summations, Vectorization, and Reproducibility Exascale Reproducibility Scalable Computing W

Ilkay Altintas

Ilkay Altintas San Diego Supercomputer Center Biography Dr. Ilkay Altintas is the Chief Data Science Officer at the San Diego Supercomputer Center (SDSC), University of California San Diego, where she is also the Founder and Director for the Workflows for Data Science Center of Excellence and a Fellow of the Halicioglu Data Scie

Neil Chue Hong

Neil Chue Hong University of Edinburgh Software Sustainability Institute Biography Neil is the founding Director of the Software Sustainability Institute, representing the Institute and UK researchers at a national and international level. His current research is in barriers and incentives in research software ecosystems and the role of sof

Brett Neuman

Brett Neuman Los Alamos National Laboratory Presentations Workshop Fast, Good, and Repeatable: Summations, Vectorization, and Reproducibility Exascale Reproducibility Scalable Computing W

Richard S. Canon

Richard S. Canon Lawrence Berkeley National Laboratory Lawrence Berkeley National Laboratory Biography Shane Canon is a Senior Engineer at Lawrence Berkeley Lab where he works in the NERSC Supercomputing Facility. Over Shane’s 20 year career, he has focused on enabling scientists to conduct breakthrough science using large-scale systems i

Pablo de Oliveira Castro

Pablo de Oliveira Castro University of Versailles Presentations Workshop Comparing Perturbation Models for Evaluating Stability of Post-Processing Pipelines in Neuroimaging Exascale Reproducibility Scalable Computing W

Laura Monroe

Laura Monroe Los Alamos National Laboratory Presentations Workshop Fast, Good, and Repeatable: Summations, Vectorization, and Reproducibility Exascale Reproducibility Scalable Computing W

Jay Lofstead

Jay Lofstead Sandia National Laboratories Biography Dr. Jay Lofstead is a Principal Member of Technical Staff at Sandia National Laboratories. His work focuses on infrastructure to support all varieties of simulation, scientific, and engineering workflows with a strong emphasis on IO, middleware, storage, transactions, operating system featu

Lorena Barba

Lorena Barba George Washington University Biography Lorena A. Barba is professor of mechanical and aerospace engineering at the George Washington University in Washington, DC. She holds a PhD in aeronautics from the California Institute of Technology and BSc/PEng degrees in mechanical engineering from Universidad Técnica Federico Santa María

Andrew Younge

Andrew Younge Sandia National Laboratories Biography Andrew J. Younge is a Senior Member of Technical Staff in the Scalable System Software department at Sandia National Laboratories. He currently serves as the Lead PI for the Supercontainers project under the DOE Exascale Computing Project and is a key contributor to the Astra system, the

Allison Baker

Allison Baker National Center for Atmospheric Research (NCAR) Biography Allison Baker is a Project Scientist III at the National Center for Atmospheric Research (NCAR). Her research interests include high-performance computing, performance analysis, iterative linear solvers, Earth System models, data compression, and verification techniques.

Alma Dimnaku

Alma Dimnaku NetApp Inc Presentations Paper SSD Failures in the Field: Symptoms, Causes, and Prediction Models Best Practices Energy Exascale Machine Learning Memory Modelling Networks Performance Power Reliability Reproducibility TP

Sudharshan Vazhkudai

Sudharshan Vazhkudai Oak Ridge National Laboratory Presentations Paper End-to-End I/O Portfolio for the Summit Supercomputing Ecosystem Architectures Data Analytics Data Management I/O Monitoring TP Workshop Applying Machine Learning to Understand the Write Performance of Large-Scale Parallel Filesystems Big Data Data Analytics Data Management Storage W Chair of Sessions Pa

Nick Johnson

Nick Johnson Edinburgh Parallel Computing Centre Biography Dr Nick Johnson is an Architect at EPCC and is involved in the H2020 FET-HPC NEXTGenIO project. Prior to this he was involved with the FP7 project Adept, which investigated power and energy consumption in parallel software and hardware where he co-designed the software and hardware n

Cindy Rubio-González

Cindy Rubio-González University of California, Davis Biography Cindy Rubio-Gonzalez is an Assistant Professor of Computer Science at the University of California, Davis. Prior to that position, she was a Postdoctoral Researcher at the University of California, Berkeley. She received her Ph.D. in Computer Science from the University of Wiscon

Richard S. Canon

Richard S. Canon Lawrence Berkeley National Laboratory Lawrence Berkeley National Laboratory Biography Shane Canon is a Senior Engineer at Lawrence Berkeley Lab where he works in the NERSC Supercomputing Facility. Over Shane’s 20 year career, he has focused on enabling scientists to conduct breakthrough science using large-scale systems i

Ignacio Laguna

Ignacio Laguna Lawrence Livermore National Laboratory Lawrence Livermore National Laboratory Biography Ignacio Laguna is a Computer Scientist at the Center for Applied Scientific Computing (CASC) at the Lawrence Livermore National Laboratory (LLNL), California. His main area of research is programing models and systems for high-performance

Christian Herold

Christian Herold Technical University Dresden Biography Christian Herold is a computer scientist at the Center for Information Services and High Performance Computing at Technische Universitaet Dresden, Germany with a focus on software performance measurement and analysis. He specializes in the field of performance tools and is involved in

Todd Gamblin

Todd Gamblin Lawrence Livermore National Laboratory Biography 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

Stef Graillat

Stef Graillat Sorbonne University Presentations Workshop Numerical Reproducibility Based on Minimal-Precision Validation Exascale Reproducibility Scalable Computing W Posters Research Posters Poster 134: Minimal-Precision Computing for High-Performance, Energy-Efficient, and Reliable Computations TP EX EXH

KBase: A Platform for Reproducible Bioinformatics Research

Description Reproducibility is a core tenet of the scientific process, yet it remains elusive for much of the sophisticated analysis required in modern science. In this paper, we describe how reproducibility is addressed in the KBase platform, a web-based platform for performing sophisticated analysis of biological data with the goal of enabling reproducible, predictive biology. We give an over

Poster 36: Modeling Non-Determinism in HPC Applications

Description As HPC applications migrate from the petascale systems of today to the exascale systems of tomorrow, the increasing need to embrace asynchronous, irregular, and dynamic communication patterns will lead to a corresponding decrease in application-level determinism. Two critical challenges emerge from this trend. First, unchecked non-determinism coupled with the non-associativity of floa

Containers in HPC

Description No longer an experimental topic, containers are here to stay in HPC. They offer software portability, improved collaboration, and data reproducibility. A variety of tools (e.g. Docker, Shifter, Singularity, Podman) exist for users who want to incorporate containers into their workflows, but oftentimes they may not know where to start. This tutorial will cover the basics of creating a

GPCNeT: Designing a Benchmark Suite for Inducing and Measuring Contention in HPC Networks

Description Network congestion is one of the biggest problems facing HPC systems today, affecting system throughput, performance, user experience, and reproducibility. Congestion manifests as run-to-run variability due to contention for shared resources (like filesystems) or routes between compute endpoints. Despite its significance, current network benchmarks fail to proxy the real-world network

SSD Failures in the Field: Symptoms, Causes, and Prediction Models

Description In recent years, solid state drives (SSDs) have become a staple of high-performance data centers for their speed and energy efficiency. In this work, we study the failure characteristics of 30,000 drives from a Google data center spanning six years. We characterize the workload conditions that lead to failures and illustrate that their root causes differ from common expectation but re

Poster 134: Minimal-Precision Computing for High-Performance, Energy-Efficient, and Reliable Computations

Description In numerical computations, the precision of floating-point computations is a key factor to determine the performance (speed and energy-efficiency) as well as the reliability (accuracy and reproducibility). However, the precision generally plays a contrary role for both. Therefore, the ultimate concept for maximizing both at the same time is the minimal-precision computation through pr

The 2019 International Workshop on Software Engineering for HPC-Enabled Research (SE-HER 2019)

Description Developers who build research software for High Performance Computing (HPC) or High Performance Data Analysis/Analytics (HPDA) face software engineering (SE) challenges at scales not often addressed by traditional SE approaches. For example, HPC and HPDA software developers must solve reliability, availability, and maintainability problems at extreme scales, consider reproducibility,

2019 IEEE Sidney Fernbach Award

Description How the Julia Language Can Fulfill the Promise of Supercomputing During the first phase of HPC, the emphasis has been on performance above all else. The thinking that carried the day was that you can hack hard enough, bring up performance, and earn your brownie points. The Julia language, through abstractions and multiple dispatch technology, is making it possible to build supercom

The National Academies’ Report on Reproducibility and Replicability in Science: Inspirations for the SC Reproducibility Initiative

Description This BoF will disseminate the findings and recommendations of the NASEM report on Reproducibility and Replicability in Science, making connections with the SC Reproducibility Initiative. It will seed the community with ideas for taking inspiration from the report’s recommendations for the conference to continue leading in the computing community, increasing the transparency of researc

Debugging and Optimization of HPC Programs with the Verrou Tool

Description The analysis of Floating-Point-related issues in HPC codes is becoming a topic of major interest: parallel computing and code optimization often break the reproducibility of numerical results across machines, compilers and even executions of the same program. This paper presents how the Verrou tool can help during all stages of the Floating-Point analysis of HPC codes: diagnostic, de

Comparing GPU Power and Frequency Capping: A Case Study with the MuMMI Workflow

Description Accomplishing the goal of exascale computing under a potential power limit requires HPC clusters to maximize both parallel efficiency and power efficiency. As modern HPC systems embark on a trend toward extreme heterogeneity leveraging multiple GPUs per node, power management becomes even more challenging, especially when catering to scientific workflows with co-scheduled components.

A Modular Course on Developing Research Software

Description This talk describes the motivation and design of learning modules for teaching best practices for developing research software and practical computational science. These modules have been offered twice as a 10-week graduate course in an engineering program, although the content applies broadly to any field of scientific and/or engineering research where software may be developed. Topi

Container Computing for HPC and Scientific Workflows

Description Container computing has revolutionized the way applications are developed and delivered. It offers opportunities that never existed before for significantly improving efficiency of scientific workflows and easily moving these workflows from the laptop to the supercomputer. Tools like Docker, Shifter, Singularity and Charliecloud enable a new paradigm for scientific and technical compu

Computational Reproducibility at Exascale 2019 (CRE2019)

Description Reproducibility is an important concern in all areas of computation. As such, computational reproducibility is receiving increasing interest from a variety of parties who are concerned with different aspects of computational reproducibility. Computational reproducibility encompasses several concerns including the sharing of code and data, as well as reproducible numerical results whic

Contained Chaos: Quality Assurance for the Community Earth System Model

Description State-of-the-science climate model are valuable tools for understanding past and present climates and are particularly vital for addressing otherwise intractable questions about future climate scenarios. Because the simulation output may affect societal responses to the changing climate, maintaining model confidence and reliability is critical for institutions like the National Cente

CRE2019 Morning Break

Description Event Type Workshop Registration Categories W Tags Exascale Reproducibility Scalable Computing

Better Scientific Software

Description The computational science and engineering (CSE) community is in the midst of an extremely challenging period created by the confluence of disruptive changes in computing architectures, demand for greater scientific reproducibility, and new opportunities for greatly improved simulation capabilities, especially through coupling physics and scales. Computer architecture changes require

Performance Optimality or Reproducibility: That Is the Question

Description The era of extremely heterogeneous supercomputing brings with itself the devil of increased performance variation and reduced reproducibility. There is a lack of understanding in the HPC community on how the simultaneous consideration of network traffic, power limits, concurrency tuning, and interference from other jobs impacts application performance. In this paper, we design a met

SuperCompCloud: Workshop on Interoperability of Supercomputing and Cloud Technologies

Description Exascale computing initiatives are expected to enable breakthroughs for multiple scientific disciplines. Increasingly these systems may utilize cloud technologies, enabling complex and distributed workflows that can improve not only scientific productivity, but accessibility of resources to a wide range of communities. Such an integrated and seamlessly orchestrated system for supercom

WACCPD Best Paper Award

Description From all accepted submissions that included reproducibility information, the WACCPD chairs award the best paper. Presenters Sandra Wienke Sridutt Bhalachandra Event Type Workshop Registration Categories W Tags Accelerators Parallel Application Frameworks Parallel Programming Languages, Libraries, and Models Scientific Computing Software Engineering

Deep Learning on Supercomputers

Description The Deep Learning (DL) on Supercomputers workshop provides a forum for practitioners working on any and all aspects of DL for science and engineering in the High Performance Computing (HPC) context to present their latest research results and development, deployment, and application experiences. The general theme of this workshop series is the intersection of DL and HPC. Its scope enc

Next Generation Disaster Intelligence Using the Continuum of Computing and Data Technologies

Description Modeling of the extent and dynamics of evolving plethora of environmental hazards, and their socio-economic and human impacts, is a data-driven discipline with a vibrant scientific community of computational modeling, remote sensing, data science, technology, and social science experts, driven by the urgent societal need to mitigate the rising frequency and severity of hazards. Howeve

Floating-Point Analysis and Reproducibility Tools for Scientific Software

Description While scientific software is widely used in several science and engineering disciplines, developing accurate and reliable scientific software is notoriously difficult. One of the most serious difficulties comes from dealing with floating-point arithmetic to perform numerical computations. Round-off errors occur and accumulate at all levels of computation, and compiler optimizations an

Evaluation and Benchmarking of Singularity MPI Containers on EU Research e-Infrastructure

Description Linux Containers with the build-once run-anywhere principle have gained huge attention in the research community where portability and reproducibility are key concerns. Unlike virtual machines (VMs), containers run the underlying host OS kernel. The container filesystem can include all necessary non-default prerequisites to run the container application at unaltered performance. For t

An Early Evaluation of Intel’s Optane DC Persistent Memory Module and Its Impact on High-Performance Scientific Applications

Description Memory and I/O performance bottlenecks in supercomputing simulations are two key challenges that must be addressed on the road to Exascale. The new byte-addressable persistent non-volatile memory technology from Intel, DCPMM, promises to be an exciting opportunity to break with the status quo, with unprecedented levels of capacity at near-DRAM speeds. Here, we explore the potential of

Panel Discussion

Description Panelists Howard Bushouse Peter Coveney Thorsten Hoefler Thomas Ludwig Line Pouchard Event Type Workshop Registration Categories W Tags Exascale Reproducibility Scalable Computing

Containers and New Orchestration Paradigms for Isolated Environments in HPC (CANOPIE HPC)

Description We are pleased to introduce the 1st International Workshop on Containers and New Orchestration Paradigms for Isolated Environments in HPC (CANOPIE HPC), to be hosted at SC19: The International Conference for High Performance Computing, Networking, Storage and Analysis. The objective of this workshop is to serve as the principal venue for leaders in the field to stimulate research and i

SuperCompCloud: Workshop on Interoperability of Supercomputing and Cloud Technologies

Description Exascale computing initiatives are expected to enable breakthroughs for multiple scientific disciplines. Increasingly these systems may utilize cloud technologies, enabling complex and distributed workflows that can improve not only scientific productivity, but accessibility of resources to a wide range of communities. Such an integrated and seamlessly orchestrated system for supercomp

Improving Next-Generation Performance and Resilience

Presentations SSD Failures in the Field: Symptoms, Causes, and Prediction Models Authors Jacob Alter Ji Xue Alma Dimnaku Evgenia Smirni An Early Evaluation of Intel’s Optane DC Persistent Memory Module and Its Impact on High-Performance Scientific Applications Authors Michèle Weiland Holger Brunst Tiago Quintino Nick

Containers in HPC

Presentations Containers in HPC Presenters Brian Skjerven Mark Gray Event Type Tutorial Registration Categories TUT Tags Containers Reproducibility Workflows

The 2019 International Workshop on Software Engineering for HPC-Enabled Research (SE-HER 2019)

Description Developers who build research software for High Performance Computing (HPC) or High Performance Data Analysis/Analytics (HPDA) face software engineering (SE) challenges at scales not often addressed by traditional SE approaches. For example, HPC and HPDA software developers must solve reliability, availability, and maintainability problems at extreme scales, consider reproducibility, u

Floating-Point Analysis and Reproducibility Tools for Scientific Software

Presentations Floating-Point Analysis and Reproducibility Tools for Scientific Software Presenters Ignacio Laguna Ganesh Gopalakrishnan Michael Bentley Ian Briggs Michael O. Lam Cindy Rubio-González Event Type Tutorial Registration Categories TUT Tags Floating Point Reproducibility Software Engineering

Computational Reproducibility at Exascale 2019 (CRE2019)

Description Reproducibility is an important concern in all areas of computation. As such, computational reproducibility is receiving increasing interest from a variety of parties who are concerned with different aspects of computational reproducibility. Computational reproducibility encompasses several concerns including the sharing of code and data, as well as reproducible numerical results which

Deep Learning on Supercomputers

Description The Deep Learning (DL) on Supercomputers workshop provides a forum for practitioners working on any and all aspects of DL for science and engineering in the High Performance Computing (HPC) context to present their latest research results and development, deployment, and application experiences. The general theme of this workshop series is the intersection of DL and HPC. Its scope enco

University of California, Davis

University of California, Davis Contributors Ayaz Akram David H. Bailey Xiaoliang Chen Yuxin Chen James P. Crutchfield Kwan-Liu Ma John Owens Roberto Proietti Cindy Rubio-González Adam Rupe Mohammad Sadoghi Yu Shang Fnu Shilpika Xian Xiao SJ Ben Yoo Yu Zhang Dongfang Zhao Session Chairs Cindy Rubio-González Presentations Workshop 3nd International Worksho

University of Utah

University of Utah Contributors Michael Bentley Ian Briggs Thomas Cheatham III Milind Deo Dmitry Duplyakin Milinda Fernando Ganesh Gopalakrishnan Jan Goral Mary Hall Masado Ishii Jinsung Kim Robert King Adam K. Kochanski Rui Li Derek V. Mallia Pavel Panchekha Daniel Reed P. Sadayappan Hari Sundar Tuowen Zhao Presentations Paper An Efficient Mixed-Mode Represen

Space Telescope Science Institute

Space Telescope Science Institute Contributors Howard Bushouse Howard Bushouse Presentations Workshop Panel Discussion Exascale Reproducibility Scalable Computing W Workshop Reproducibility and Provenance of James Webb Space Telescope Data Products Exascale Reproducibility Scalable Computing W

Sandia National Laboratories

Sandia National Laboratories Contributors Omar Aaziz Anthony Agelestos Burak Aksar Jonathan W. Berry Jim Brandt Ron Brightwell Jeanine Cook Matthew Curry Stefan Domino Matthew G. F. Dosanjh Kurt Ferreira Ann Gentile Ryan Grant Simon D. Hammond Michael Heroux Mark Hoemmen David S. Hollman Dan Ibanez Samuel Knight James Laros Margaret Lawson Vitus Leung Scott Levy Jay Lof

Technical University Dresden

Technical University Dresden Contributors Mario Bielert Holger Brunst Jan Frenzel Daniel Hackenberg Christian Herold Franz Höpfner Thomas Ilsche René Jäkel Maximilian Knespel Wolfgang E. Nagel Robert Schöne Ronny Tschueter Matthias Weber William Williams Presentations Paper An Early Evaluation of Intel’s Optane DC Persistent Memory Module and Its Impact on High-Perf

New York University

New York University Contributors Kyle Cranmer Juliana Freire Suzanne McIntosh Session Chairs Suzanne McIntosh Presentations Paper Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale Deep Learning Energy Extreme Scale Computing Machine Learning Performance Power Resource Management Runtime Systems Simulation TP BP Finalist Workshop Internati

Western Washington University

Western Washington University Contributors Alexis Ayala Tanzima Z. Islam Quentin Jensen Presentations Paper Performance Optimality or Reproducibility: That Is the Question Best Practices Energy Exascale Machine Learning Memory Modelling Networks Performance Power Reliability Reproducibility TP Workshop Toward a Programmable Analysis and Visualization Framework for Int

George Washington University

George Washington University Contributors Lorena Barba Presentations Birds of a Feather The National Academies’ Report on Reproducibility and Replicability in Science: Inspirations for the SC Reproducibility Initiative Government Strategies, Programs, and Funding Reproducibility TP EX EXH

ETH Zurich

ETH Zurich Contributors Sadaf R. Alam Tal Ben-Nun Luca Benini Maciej Besta Marcin Copik Johannes de Fine Licht Tiziano De Matteis Daniele De Sensi Salvatore Di Girolamo Guillermo Indalecio Fernandez Robert Gerstenberger Lukas Gianinazzi Thorsten Hoefler Guillermo Indalecio Fernandez Andrey Ivanov Marko Kabic Andreas Kurth Grzegorz Kwasniewski Shigang Li Mathieu Luisier Yis

National Energy Research Scientific Computing Center (NERSC)

National Energy Research Scientific Computing Center (NERSC) Contributors Deborah Bard Jeff Broughton Shane Canon Jack Deslippe Rahulkumar Gayatri Richard Gerber Kevin Gott Rebecca Hartman-Baker Yun (Helen) He Thorsten Kurth Craig Lant Kelly L. Rowland Abe Singer David Skinner Cory Snavely Nicholas James Wright Charlene Yang Session Chairs Rebecca Hartman-Baker Kri

Space Telescope Science Institute (STScI)

Space Telescope Science Institute (STScI) Presentations Workshop Computational Reproducibility at Exascale 2019 (CRE2019) Exascale Reproducibility Scalable Computing W

National Institute of Standards and Technology (NIST)

National Institute of Standards and Technology (NIST) Contributors Robert Bohn Walid Keyrouz Michael Mascagni Bradley Pearlman Michael A. Perlin Barry Schneider Session Chairs Walid Keyrouz Michael V. Mascagni Presentations Birds of a Feather Cloud Federation for Large-Scale Collaborations Cloud Federation Clouds and Distributed Computing Collaborative Environmen

Pawsey Supercomputing Center

Pawsey Supercomputing Center Contributors Maciej Cytowski Mark Gray Brian Skjerven Presentations Tutorial Containers in HPC Containers Reproducibility Workflows TUT Birds of a Feather Emerging Technologies and HPC Education, Outreach, and Training: Challenges and Opportunities Education SigHPC Chapter Training TP EX EXH Booth 2101 Exhibitor Description The Paws

Los Alamos National Laboratory

Los Alamos National Laboratory Contributors James P. Ahrens Robert Bird Ayan Biswas David Bonnie Guangye Chen Lukasz Cincio Nathan DeBardeleben Hristo Djidjev Andy Dubois Kody J. Everson Charles R. Ferenbaugh Sandrasegaram Gnanakaran Xava A. Grooms Pascal Grosset Patricia Grubel Jason Hick Latchesar Ionkov Brendan K. Krueger Jeff Kuehn Michael Lang Maria Francine Lapid Yi

James Madison University

James Madison University Contributors Michael O. Lam Presentations Tutorial Floating-Point Analysis and Reproducibility Tools for Scientific Software Floating Point Reproducibility Software Engineering TUT Workshop Tool Integration for Source-Level Mixed Precision Correctness Debugging Floating Point Mixed-precision Reliability Verification W

Florida State University

Florida State University Contributors Saptarshi Bhowmik Fahim Tahmid Chowdhury Tonmoy Dey Michael Mascagni Md Shafayat Rahman Rupak Roy Yevgeniy Ryasnianskiy Weikuan Yu Xin Yuan Session Chairs Michael V. Mascagni Presentations Workshop Computational Reproducibility at Exascale 2019 (CRE2019) Exascale Reproducibility Scalable Computing W Posters Research Posters

University College London

University College London Contributors Peter Coveney Bradley E. Treeby Georgios Zervas Presentations Workshop Panel Discussion Exascale Reproducibility Scalable Computing W Posters Research Posters Poster 116: Advancements in Ultrasound Simulations Enabled by High-Bandwidth GPU Interconnects TP EX EXH Posters Research Posters Poster 63: Adaptive Execution Planning in Bio

Brookhaven National Laboratory

Brookhaven National Laboratory Contributors Barbara Chapman Adolfy Hoisie Shantenu Jha Vivek Kale Kerstin Kleese Van Dam Lingda Li Abid Malik Michael McGuigan Abdullah B. Nauman Line Pouchard Yihui Ren Shinjae Yoo Session Chairs Barbara M. Chapman Presentations Workshop 3rd International Workshop on Emerging Parallel and Distributed Runtime Systems and Middlew

Lawrence Livermore National Laboratory

Lawrence Livermore National Laboratory Contributors Bob Anderson Anna Maria Bailey Peter Barnes Sorin Bastea Gregory Becker David Beckingsale Tom Benson Adam Bertsch Abhinav Bhatele Harsh Bhatia Barna Bihari Robert Blake David Boehme Jamie A. Bramwell Jim Brase Peer-Timo Bremer Stephanie Brink Jason Burmark Jean-Sylvain Camier Timothy S. Carpenter Barry Chen Jaemin Choi

Lawrence Berkeley National Laboratory

Lawrence Berkeley National Laboratory Contributors Deborah Agarwal Abdullah Al-Mamun Ann Almgren Diana Amorim Brian Austin Scott Baden David H. Bailey Deborah Bard Harold Barnard Elizabeth Bautista John Bell E Wes Bethel Sridutt Bhalachandra Wahid Bhimji Ludovico Bianchi Jay R. Bolton Dan Bonachea Benjamin A. Brock Jeff Broughton Aydın Buluç Anastasia Butko Suren Byn

University of Versailles

University of Versailles Contributors Pablo de Oliveira Castro Presentations Workshop Comparing Perturbation Models for Evaluating Stability of Post-Processing Pipelines in Neuroimaging Exascale Reproducibility Scalable Computing W

RIKEN Center for Computational Science (R-CCS)

RIKEN Center for Computational Science (R-CCS) Contributors Kazuto Ando Jens Domke Kohei Fujita Balazs Gerofi Jian Guo Jens Huthmann Toshiyuki Imamura Takuya Ina Hajime Inaoka Yutaka Ishikawa Nobuyasu Ito Yuetsu Kodama Kazuki Koiso Atsushi Koshiba Kiyoshi Kumahata Akiyoshi Kuroda Satoshi Matsuoka Kazuo Minami Takaaki Miyajima Daichi Mukunoki Kengo Nakajima Jorji Nonaka K

NetApp Inc

NetApp Inc Contributors Alma Dimnaku Presentations Paper SSD Failures in the Field: Symptoms, Causes, and Prediction Models Best Practices Energy Exascale Machine Learning Memory Modelling Networks Performance Power Reliability Reproducibility TP Booth 249 Exhibitor Description Throughout the world, leading organizations count on NetApp for software, systems and ser

College of William & Mary

College of William & Mary Contributors Jacob Alter Shuyin Jiao Xu Liu Bin Ren Evgenia Smirni Pengfei Su Ji Xue Presentations Paper MemXCT: Memory-Centric X-Ray CT Reconstruction with Massive Parallelization Algorithms Applications Parallel Application Frameworks Scalable Computing TP Paper Pinpointing Performance Inefficiencies via Lightweight Variance Profiling B

Edinburgh Parallel Computing Centre

Edinburgh Parallel Computing Centre Contributors Neelofer Banglawala Nick Brown Oliver Brown Jonathan Mark Bull Philip Cass Weronika Filinger Daniel Holmes Adrian Jackson Maurice C. Jamieson Nick Johnson Kieran Leach Craig Manzi Rupert Nash Mark Parsons Bianca Prodan Anna Roubickova Michèle Weiland Session Chairs Nick Brown Presentations Paper An Early Ev

Sorbonne University

Sorbonne University Contributors Stef Graillat Roman Iakymchuk Fabienne Jézéquel Julien Tierny Jules Vidal Presentations Workshop Numerical Reproducibility Based on Minimal-Precision Validation Exascale Reproducibility Scalable Computing W Posters Research Posters Poster 134: Minimal-Precision Computing for High-Performance, Energy-Efficient, and Reliable Computations TP

Oak Ridge National Laboratory

Oak Ridge National Laboratory Contributors Scott Atchley Ashley Barker David Bernholdt Debsindhu Bhowmik Christopher Brumgard Junghoon Chae Jieyang Chen Jong Choi Mark Coletti Ethan T. Coon Ed D’Azevedo Diego Del-Castillo-Negrete Abhishek Dubey Wael Elwasif Chistrian Engelmann Kate Evans Shubhankar Gahlot Al Geist William Godoy John Gounley David L. Green Steven Hamilton

European Centre for Medium-Range Weather Forecasts

European Centre for Medium-Range Weather Forecasts Contributors Antonino Bonanni Olivier Iffrig Tiago Quintino Simon Smart Presentations Paper An Early Evaluation of Intel’s Optane DC Persistent Memory Module and Its Impact on High-Performance Scientific Applications Best Practices Energy Exascale Machine Learning Memory Modelling Networks Performance Power Reliability Reprod

Intel Corporation

Intel Corporation Contributors Nesreen Ahmed Jeff Amstutz Michael Anderson Sasikanth Avancha Kunal Banerjee Fabio Baruffa Aaron Blakeman James Brodman Christopher Cantalupo Ralph Castain Mohamad Chaarawi James Dinan Jonathan Eastep Vladislav Epifanov John Freeman Evangelos Georganas Kazushige Goto Johannes Günther Jeff R. Hammond Alexander Heinecke Greg Henry Jin Hong Ha

McGill University

McGill University Contributors Shawn T. Brown Alan C. Evans Gregory Kiar Pierre Rioux Presentations Workshop Comparing Perturbation Models for Evaluating Stability of Post-Processing Pipelines in Neuroimaging Exascale Reproducibility Scalable Computing W

Concordia University

Concordia University Contributors Mathieu Dugré Tristan Glatard Valérie Hayot-Sasson Presentations Workshop A Performance Comparison of Dask and Apache Spark for Data-Intensive Neuroimaging Pipelines Extreme Scale Computing Scalable Computing Scientific Workflows W Workshop Comparing Perturbation Models for Evaluating Stability of Post-Processing Pipelines in Neuroimaging Ex

German Climate Computing Center

German Climate Computing Center Contributors Thomas Ludwig Presentations Workshop Panel Discussion Exascale Reproducibility Scalable Computing W

Contributors

A Tanuj K. Aasawat RIKEN Japan Posters Poster 59: Accelerating BFS and SSSP on a NUMA Machine for the Graph500 Challenge Omar Aaziz Sandia National Laboratories United States of America Workshop Fine-Grained Analysis of Communication Similarity between Real and Proxy Applications Posters Poster 150: A Machine Learning Approach to Understanding HPC Application Perfo

Full Program

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