%0 Conference Paper %B 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2021) %D 2021 %T Distributed-Memory Multi-GPU Block-Sparse Tensor Contraction for Electronic Structure %A Thomas Herault %A Yves Robert %A George Bosilca %A Robert Harrison %A Cannada Lewis %A Edward Valeev %A Jack Dongarra %K block-sparse matrix multiplication %K distributed-memory %K Electronic structure %K multi-GPU node %K parsec %K tensor contraction %X Many domains of scientific simulation (chemistry, condensed matter physics, data science) increasingly eschew dense tensors for block-sparse tensors, sometimes with additional structure (recursive hierarchy, rank sparsity, etc.). Distributed-memory parallel computation with block-sparse tensorial data is paramount to minimize the time-tosolution (e.g., to study dynamical problems or for real-time analysis) and to accommodate problems of realistic size that are too large to fit into the host/device memory of a single node equipped with accelerators. Unfortunately, computation with such irregular data structures is a poor match to the dominant imperative, bulk-synchronous parallel programming model. In this paper, we focus on the critical element of block-sparse tensor algebra, namely binary tensor contraction, and report on an efficient and scalable implementation using the task-focused PaRSEC runtime. High performance of the block-sparse tensor contraction on the Summit supercomputer is demonstrated for synthetic data as well as for real data involved in electronic structure simulations of unprecedented size. %B 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2021) %I IEEE %C Portland, OR %8 2021-05 %G eng %U https://hal.inria.fr/hal-02970659/document %0 Conference Paper %B 2020 IEEE/ACM 5th International Workshop on Extreme Scale Programming Models and Middleware (ESPM2) %D 2020 %T The Template Task Graph (TTG) - An Emerging Practical Dataflow Programming Paradigm for Scientific Simulation at Extreme Scale %A George Bosilca %A Robert Harrison %A Thomas Herault %A Mohammad Mahdi Javanmard %A Poornima Nookala %A Edward Valeev %K dag %K dataflow %K exascale %K graph %K High-performance computing %K workflow %X We describe TESSE, an emerging general-purpose, open-source software ecosystem that attacks the twin challenges of programmer productivity and portable performance for advanced scientific applications on modern high-performance computers. TESSE builds upon and extends the ParsecDAG/-dataflow runtime with a new Domain Specific Languages (DSL) and new integration capabilities. Motivating this work is our belief that such a dataflow model, perhaps with applications composed in domain specific languages, can overcome many of the challenges faced by a wide variety of irregular applications that are poorly served by current programming and execution models. Two such applications from many-body physics and applied mathematics are briefly explored. This paper focuses upon the Template Task Graph (TTG), which is TESSE's main C++ Api that provides a powerful work/data-flow programming model. Algorithms on spatial trees, block-sparse tensors, and wave fronts are used to illustrate the API and associated concepts, as well as to compare with related approaches. %B 2020 IEEE/ACM 5th International Workshop on Extreme Scale Programming Models and Middleware (ESPM2) %I IEEE %8 2020-11 %G eng %R https://doi.org/10.1109/ESPM251964.2020.00011 %0 Generic %D 2018 %T Tensor Contraction on Distributed Hybrid Architectures using a Task-Based Runtime System %A George Bosilca %A Damien Genet %A Robert Harrison %A Thomas Herault %A Mohammad Mahdi Javanmard %A Chong Peng %A Edward Valeev %X The needs for predictive simulation of electronic structure in chemistry and materials science calls for fast/reduced-scaling formulations of quantum n-body methods that replace the traditional dense tensors with element-, block-, rank-, and block-rank-sparse (data-sparse) tensors. The resulting, highly irregular data structures are a poor match to imperative, bulk-synchronous parallel programming style due to the dynamic nature of the problem and to the lack of clear domain decomposition to guarantee a fair load-balance. TESSE runtime and the associated programming model aim to support performance-portable composition of applications involving irregular and dynamically changing data. In this paper we report an implementation of irregular dense tensor contraction in a paradigmatic electronic structure application based on the TESSE extension of PaRSEC, a distributed hybrid task runtime system, and analyze the resulting performance on a distributed memory cluster of multi-GPU nodes. Unprecedented strong scaling and promising efficiency indicate a viable future for task-based programming of complete production-quality reduced scaling models of electronic structure. %B Innovative Computing Laboratory Technical Report %I University of Tennessee %8 2018-12 %G eng %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 Oak Ridge National Laboratory Report %D 2004 %T Cray X1 Evaluation Status Report %A Pratul Agarwal %A R. A. Alexander %A E. Apra %A Satish Balay %A Arthur S. Bland %A James Colgan %A Eduardo D'Azevedo %A Jack Dongarra %A Tom Dunigan %A Mark Fahey %A Al Geist %A M. Gordon %A Robert Harrison %A Dinesh Kaushik %A M. Krishnakumar %A Piotr Luszczek %A Tony Mezzacapa %A Jeff Nichols %A Jarek Nieplocha %A Leonid Oliker %A T. Packwood %A M. Pindzola %A Thomas C. Schulthess %A Jeffrey Vetter %A James B White %A T. Windus %A Patrick H. Worley %A Thomas Zacharia %B Oak Ridge National Laboratory Report %V /-2004/13 %8 2004-01 %G eng