%0 Journal Article %J The International Journal of High Performance Computing Applications %D 2018 %T Big Data and Extreme-Scale Computing: Pathways to Convergence - Toward a Shaping Strategy for a Future Software and Data Ecosystem for Scientific Inquiry %A Mark Asch %A Terry Moore %A Rosa M. Badia %A Micah Beck %A Pete Beckman %A Thierry Bidot %A François Bodin %A Franck Cappello %A Alok Choudhary %A Bronis R. de Supinski %A Ewa Deelman %A Jack Dongarra %A Anshu Dubey %A Geoffrey Fox %A Haohuan Fu %A Sergi Girona %A Michael Heroux %A Yutaka Ishikawa %A Kate Keahey %A David Keyes %A William T. Kramer %A Jean-François Lavignon %A Yutong Lu %A Satoshi Matsuoka %A Bernd Mohr %A Stéphane Requena %A Joel Saltz %A Thomas Schulthess %A Rick Stevens %A Martin Swany %A Alexander Szalay %A William Tang %A Gaël Varoquaux %A Jean-Pierre Vilotte %A Robert W. Wisniewski %A Zhiwei Xu %A Igor Zacharov %X Over the past four years, the Big Data and Exascale Computing (BDEC) project organized a series of five international workshops that aimed to explore the ways in which the new forms of data-centric discovery introduced by the ongoing revolution in high-end data analysis (HDA) might be integrated with the established, simulation-centric paradigm of the high-performance computing (HPC) community. Based on those meetings, we argue that the rapid proliferation of digital data generators, the unprecedented growth in the volume and diversity of the data they generate, and the intense evolution of the methods for analyzing and using that data are radically reshaping the landscape of scientific computing. The most critical problems involve the logistics of wide-area, multistage workflows that will move back and forth across the computing continuum, between the multitude of distributed sensors, instruments and other devices at the networks edge, and the centralized resources of commercial clouds and HPC centers. We suggest that the prospects for the future integration of technological infrastructures and research ecosystems need to be considered at three different levels. First, we discuss the convergence of research applications and workflows that establish a research paradigm that combines both HPC and HDA, where ongoing progress is already motivating efforts at the other two levels. Second, we offer an account of some of the problems involved with creating a converged infrastructure for peripheral environments, that is, a shared infrastructure that can be deployed throughout the network in a scalable manner to meet the highly diverse requirements for processing, communication, and buffering/storage of massive data workflows of many different scientific domains. Third, we focus on some opportunities for software ecosystem convergence in big, logically centralized facilities that execute large-scale simulations and models and/or perform large-scale data analytics. We close by offering some conclusions and recommendations for future investment and policy review. %B The International Journal of High Performance Computing Applications %V 32 %P 435–479 %8 2018-07 %G eng %N 4 %R https://doi.org/10.1177/1094342018778123 %0 Journal Article %J International Journal of High Performance Computing %D 2011 %T The International Exascale Software Project Roadmap %A Jack Dongarra %A Pete Beckman %A Terry Moore %A Patrick Aerts %A Giovanni Aloisio %A Jean-Claude Andre %A David Barkai %A Jean-Yves Berthou %A Taisuke Boku %A Bertrand Braunschweig %A Franck Cappello %A Barbara Chapman %A Xuebin Chi %A Alok Choudhary %A Sudip Dosanjh %A Thom Dunning %A Sandro Fiore %A Al Geist %A Bill Gropp %A Robert Harrison %A Mark Hereld %A Michael Heroux %A Adolfy Hoisie %A Koh Hotta %A Zhong Jin %A Yutaka Ishikawa %A Fred Johnson %A Sanjay Kale %A Richard Kenway %A David Keyes %A Bill Kramer %A Jesus Labarta %A Alain Lichnewsky %A Thomas Lippert %A Bob Lucas %A Barney MacCabe %A Satoshi Matsuoka %A Paul Messina %A Peter Michielse %A Bernd Mohr %A Matthias S. Mueller %A Wolfgang E. Nagel %A Hiroshi Nakashima %A Michael E. Papka %A Dan Reed %A Mitsuhisa Sato %A Ed Seidel %A John Shalf %A David Skinner %A Marc Snir %A Thomas Sterling %A Rick Stevens %A Fred Streitz %A Bob Sugar %A Shinji Sumimoto %A William Tang %A John Taylor %A Rajeev Thakur %A Anne Trefethen %A Mateo Valero %A Aad van der Steen %A Jeffrey Vetter %A Peg Williams %A Robert Wisniewski %A Kathy Yelick %X Over the last 20 years, the open-source community has provided more and more software on which the world’s high-performance computing systems depend for performance and productivity. The community has invested millions of dollars and years of effort to build key components. However, although the investments in these separate software elements have been tremendously valuable, a great deal of productivity has also been lost because of the lack of planning, coordination, and key integration of technologies necessary to make them work together smoothly and efficiently, both within individual petascale systems and between different systems. It seems clear that this completely uncoordinated development model will not provide the software needed to support the unprecedented parallelism required for peta/ exascale computation on millions of cores, or the flexibility required to exploit new hardware models and features, such as transactional memory, speculative execution, and graphics processing units. This report describes the work of the community to prepare for the challenges of exascale computing, ultimately combing their efforts in a coordinated International Exascale Software Project. %B International Journal of High Performance Computing %V 25 %P 3-60 %8 2011-01 %G eng %R https://doi.org/10.1177/1094342010391989 %0 Journal Article %J ACM Transactions on Mathematical Software %D 2002 %T An Updated Set of Basic Linear Algebra Subprograms (BLAS) %A Susan Blackford %A James Demmel %A Jack Dongarra %A Iain Duff %A Sven Hammarling %A Greg Henry %A Michael Heroux %A Linda Kaufman %A Andrew Lumsdaine %A Antoine Petitet %A Roldan Pozo %A Karin Remington %A Clint Whaley %B ACM Transactions on Mathematical Software %V 28 %P 135-151 %8 2002-12 %G eng %R 10.1145/567806.567807 %0 Journal Article %J (an update), submitted to ACM TOMS %D 2001 %T Basic Linear Algebra Subprograms (BLAS) %A Susan Blackford %A James Demmel %A Jack Dongarra %A Iain Duff %A Sven Hammarling %A Greg Henry %A Michael Heroux %A Linda Kaufman %A Andrew Lumsdaine %A Antoine Petitet %A Roldan Pozo %A Karin Remington %A Clint Whaley %B (an update), submitted to ACM TOMS %8 2001-02 %G eng