Table of Contents

• On the Use of Kernel Bypass Mechanisms for High-Performance Inter-container CommunicationsGabriele Ara, Luca Abeni, Tommaso Cucinotta, Carlo Vitucci. 1-12 [doi]
• Continuous-Action Reinforcement Learning for Memory Allocation in Virtualized ServersLuis A. Garrido, Rajiv Nishtala, Paul M. Carpenter. 13-24 [doi]
• Container Orchestration on HPC ClustersMarco Enrico Piras, Luca Pireddu, Marco Moro, Gianluigi Zanetti. 25-35 [doi]
• Data Pallets: Containerizing Storage for Reproducibility and TraceabilityJay F. Lofstead, Joshua Baker, Andrew Younge. 36-45 [doi]
• Sarus: Highly Scalable Docker Containers for HPC SystemsLucas Benedicic, Felipe A. Cruz, Alberto Madonna, Kean Mariotti. 46-60 [doi]
• Singularity GPU Containers Execution on HPC ClusterGiuseppa Muscianisi, Giuseppe Fiameni, Abdulrahman Azab. 61-68 [doi]
• A Multitenant Container Platform with OKD, Harbor Registry and ELKJarle Bjørgeengen. 69-79 [doi]
• Enabling GPU-Enhanced Computer Vision and Machine Learning Research Using ContainersMartial Michel, Nicholas Burnett. 80-87 [doi]
• Software and Hardware Co-design for Low-Power HPC PlatformsManolis Ploumidis, Nikolaos D. Kallimanis, Marios Asiminakis, Nikos Chrysos, Pantelis Xirouchakis, Michalis Gianoudis, Leandros Tzanakis, Nikolaos Dimou, Antonis Psistakis, Panagiotis Peristerakis, Giorgos Kalokairinos, Vassilis Papaefstathiou, Manolis Katevenis. 88-100 [doi]
• Modernizing Titan2D, a Parallel AMR Geophysical Flow Code to Support Multiple Rheologies and ExtendabilityNikolay A. Simakov, Renette L. Jones-Ivey, Ali Akhavan-Safaei, Hossein Aghakhani, Matthew D. Jones, Abani K. Patra. 101-112 [doi]
• Asynchronous AMR on Multi-GPUsMuhammed Nufail Farooqi, Tan Nguyen, Weiqun Zhang, Ann S. Almgren, John Shalf, Didem Unat. 113-123 [doi]
• Batch Solution of Small PDEs with the OPS DSLIstván Z. Reguly, Branden Moore, Tim Schmielau, Jacques Du Toit, Gihan R. Mudalige. 124-141 [doi]
• Scalable Parallelization of Stencils Using MODANabeeh Jum'ah, Julian M. Kunkel. 142-154 [doi]
• Comparing High Performance Computing Accelerator Programming ModelsSwaroop Pophale, Swen Boehm, Verónica G. Vergara Larrea. 155-168 [doi]
• Tracking User-Perceived I/O Slowdown via ProbingJulian M. Kunkel, Eugen Betke. 169-182 [doi]
• A Quantitative Approach to Architecting All-Flash Lustre File SystemsGlenn K. Lockwood, Kirill Lozinskiy, Lisa Gerhardt, Ravi Cheema, Damian Hazen, Nicholas J. Wright. 183-197 [doi]
• MBWU: Benefit Quantification for Data Access Function OffloadingJianshen Liu, Philip Kufeldt, Carlos Maltzahn. 198-213 [doi]
• Footprinting Parallel I/O - Machine Learning to Classify Application's I/O BehaviorEugen Betke, Julian M. Kunkel. 214-226 [doi]
• Adventures in NoSQL for Metadata ManagementJay F. Lofstead, Ashleigh Ryan, Margaret Lawson. 227-239 [doi]
• Towards High Performance Data Analytics for Climate ChangeSandro Fiore, Donatello Elia, Cosimo Palazzo, Fabrizio Antonio, Alessandro D'Anca, Ian T. Foster, Giovanni Aloisio. 240-257 [doi]
• An Architecture for High Performance Computing and Data Systems Using Byte-Addressable Persistent MemoryAdrian Jackson, Michèle Weiland, Mark Parsons, Bernhard Homoelle. 258-274 [doi]
• Mediating Data Center Storage Diversity in HPC Applications with FAODELPatrick M. Widener, Craig Ulmer, Scott Levy, Todd Kordenbrock, Gary Templet. 275-287 [doi]
• Predicting File Lifetimes with Machine LearningFlorent Monjalet, Thomas Leibovici. 288-299 [doi]
• An I/O Analysis of HPC Workloads on CephFS and LustreAlberto Chiusole, Stefano Cozzini, Daniel van der Ster, Massimo Lamanna, Graziano Giuliani. 300-316 [doi]
• Enabling Fast and Highly Effective FPGA Design Process Using the CAPI SNAP FrameworkAlexandre Castellane, Bruno Mesnet. 317-329 [doi]
• Scaling the Summit: Deploying the World's Fastest SupercomputerVerónica G. Vergara Larrea, Wayne Joubert, Michael J. Brim, Reuben D. Budiardja, Don Maxwell, Matthew Ezell, Christopher Zimmer 0001, Swen Boehm, Wael R. Elwasif, Sarp Oral, Chris Fuson, Daniel Pelfrey, Oscar R. Hernandez, Dustin Leverman, Jesse Hanley, Mark A. Berrill, Arnold N. Tharrington. 330-351 [doi]
• Parallelware Tools: An Experimental Evaluation on POWER SystemsManuel Arenaz, Xavier Martorell. 352-360 [doi]
• Performance Evaluation of MPI Libraries on GPU-Enabled OpenPOWER Architectures: Early ExperiencesKawthar Shafie Khorassani, Ching-Hsiang Chu, Hari Subramoni, Dhabaleswar K. Panda. 361-378 [doi]
• Exploring the Behavior of Coherent Accelerator Processor Interface (CAPI) on IBM Power8+ Architecture and FlashSystem 900Kaushik Velusamy, Smriti Prathapan, Milton Halem. 379-396 [doi]
• Porting Adaptive Ensemble Molecular Dynamics Workflows to the Summit SupercomputerJohn R. Ossyra, Ada Sedova, Arnold N. Tharrington, Frank Noé, Cecilia Clementi, Jeremy C. Smith. 397-417 [doi]
• Performance Comparison for Neuroscience Application BenchmarksAndreas Herten, Thorsten Hater, Wouter Klijn, Dirk Pleiter. 418-431 [doi]
• Evaluating POWER Architecture for Distributed Training of Generative Adversarial NetworksAhmad Hesam, Sofia Vallecorsa, Gulrukh Khattak, Federico Carminati. 432-440 [doi]
• A Study on the Performance of Reproducible ComputationsNico Bombace, Michèle Weiland. 441-451 [doi]
• Three Numerical Reproducibility Issues That Can Be Explained as Round-Off ErrorMichael Mascagni. 452-462 [doi]
• Training Multiscale-CNN for Large Microscopy Image Classification in One HourKushal Datta, Imtiaz Hossain, Sun Choi, Vikram Saletore, Kyle Ambert, William J. Godinez, Xian Zhang. 463-477 [doi]
• Benchmarking Deep Learning Infrastructures by Means of TensorFlow and ContainersAdrian Grupp, Valentin Kozlov, Isabel Campos Plasencia, Mário David, Jorge Gomes 0001, Álvaro López García. 478-489 [doi]
• MagmaDNN: Towards High-Performance Data Analytics and Machine Learning for Data-Driven Scientific ComputingDaniel Nichols, Nathalie-Sofia Tomov, Frank Betancourt, Stanimire Tomov, Kwai Wong, Jack J. Dongarra. 490-503 [doi]
• Open OnDemand: HPC for EveryoneRobert E. Settlage, Alan Chalker, Eric Franz, Douglas Johnson, Steven M. Gallo, Edgar Moore, David E. Hudak. 504-513 [doi]
• Highly Interactive, Steered Scientific Workflows on HPC Systems: Optimizing Design SolutionsJohn R. Ossyra, Ada Sedova, Matthew B. Baker, Jeremy C. Smith. 514-527 [doi]
• The Role of Interactive Super-Computing in Using HPC for Urgent Decision MakingNick Brown, Rupert Nash, Gordon Gibb, Bianca Prodan, Max Kontak, Vyacheslav Olshevsky, Wei Der Chien. 528-540 [doi]
• Deep Learning at Scale for Subgrid Modeling in Turbulent Flows: Regression and ReconstructionMathis Bode, Michael Gauding, Konstantin Kleinheinz, Heinz Pitsch. 541-560 [doi]
• Using FPGAs to Accelerate HPC and Data Analytics on Intel-Based SystemsThomas Steinke, Estela Suarez, Taisuke Boku, Nalini Kumar, David E. Martin. 561-566 [doi]
• Exploring the Acceleration of the Met Office NERC Cloud Model Using FPGAsNick Brown. 567-586 [doi]
• ® FPGAsChao Jiang, Dave Ojika, Thorsten Kurth, Prabhat, Sofia Vallecorsa, Bhavesh Patel, Herman Lam. 587-600 [doi]
• In-Situ Data Reduction via Incoherent SensingKai Zhang, Alireza Entezari. 601-611 [doi]
• In-Situ Processing in Climate ScienceNiklas Röber, Jan Frederik Engels. 612-622 [doi]
• Distributed Out-of-Core Approach for In-Situ Volume Rendering of Massive DatasetJonathan Sarton, Yannick Rémion, Laurent Lucas. 623-633 [doi]
• Leveraging NVIDIA Omniverse for In Situ VisualizationMathias Hummel, Kees van Kooten. 634-642 [doi]
• Hands-On Research and Training in High Performance Data Sciences, Data Analytics, and Machine Learning for Emerging EnvironmentsKwai Wong, Stanimire Tomov, Jack J. Dongarra. 643-655 [doi]