{"id":15059,"date":"2024-01-18T20:16:14","date_gmt":"2024-01-18T19:16:14","guid":{"rendered":"https:\/\/sano.science\/?post_type=seminars&p=15059"},"modified":"2024-01-22T15:30:06","modified_gmt":"2024-01-22T14:30:06","slug":"120-community-oriented-software-development-for-exascale","status":"publish","type":"seminars","link":"https:\/\/sano.science\/seminars\/120-community-oriented-software-development-for-exascale\/","title":{"rendered":"120. Community-Oriented Software Development for Exascale in ECP and xSDK\u00a0Projects"},"content":{"rendered":"\n
Abstract<\/h2>\n\n\n\n
The development of increasingly complex computer architectures and software ecosystems continues. Applications that incorporate multiphysics modeling as well as the coupling of simulation and data analytics increasingly require the combined use of software packages developed by diverse, independent teams throughout the HPC community. The Extreme-scale Scienti\ufb01c Software Development Kit (xSDK) is being developed to provide coordinated infrastructure for independent mathematical libraries to support the productive and efficient development of high-quality applications. This webinar will discuss the development and impact of xSDK community policies, which constitute an integral part of the project and have been defined to achieve improved code quality and compatibility across xSDK member packages and a sustainable software ecosystem.<\/p>\n\n\n\n
<\/div>\n\n\n\n
About the author<\/h2>\n\n\n\n
Piotr Luszczek is a Staff Scientist at MIT Lincoln Lab and a Research Associate Professor at the Innovative Computing Laboratory in the University of Tennessee. He earned his MSc in Computer Science from AGH University of Science and Technology in Krakow, Poland, and his PhD in Computer Science from the University of Tennessee Knoxville. His research interests include numerical linear algebra for high-performance computing, automated performance engineering for hardware accelerators, and stochastic models for performance. He has decades of experience developing high performance numerical software for large scale, distributed memory systems with multicore processors and GPU accelerators. Recently, Piotr served a co-PI for the ECP xSDK project whose main goal was to improve access to the world-class software on the Exascale machines.<\/p>\n\n\n\n
Piotr Luszczek \u2013 Staff Scientist MIT Lincoln Lab, USA and Research Associate Professor Innovative Computing Laboratory Department of Computer Science University of Tennessee, USA<\/p>\n","protected":false},"featured_media":0,"template":"","class_list":["post-15059","seminars","type-seminars","status-publish","hentry"],"yoast_head":"\n
120. Community-Oriented Software Development for Exascale in ECP and xSDK\u00a0Projects - Centre for Computational Personalized Medicine<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sano.science\/seminars\/120-community-oriented-software-development-for-exascale\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"120. 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Applications that incorporate multiphysics modeling as well as the coupling of simulation and data analytics increasingly require the combined use of software packages developed by diverse, independent teams throughout the HPC community. The Extreme-scale Scienti\ufb01c Software Development Kit (xSDK) is being developed to provide coordinated infrastructure for independent mathematical libraries to support the productive and efficient development of high-quality applications. This webinar will discuss the development and impact of xSDK community policies, which constitute an integral part of the project and have been defined to achieve improved code quality and compatibility across xSDK member packages and a sustainable software ecosystem.<\/p>\n"]},{"blockName":"core\/spacer","attrs":{"height":"50px","epAnimationGeneratedClass":"edplus_anim-tnSS40","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n","innerContent":["\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n"]},{"blockName":"core\/heading","attrs":{"epAnimationGeneratedClass":"edplus_anim-jFat2H","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<h2 class=\"wp-block-heading eplus-wrapper\">About the author<\/h2>\n","innerContent":["\n<h2 class=\"wp-block-heading eplus-wrapper\">About the author<\/h2>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-AOvKVe","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\">Piotr Luszczek is a Staff Scientist at MIT Lincoln Lab and a Research Associate Professor at the Innovative Computing Laboratory in the University of Tennessee. He earned his MSc in Computer Science from AGH University of Science and Technology in Krakow, Poland, and his PhD in Computer Science from the University of Tennessee Knoxville. His research interests include numerical linear algebra for high-performance computing, automated performance engineering for hardware accelerators, and stochastic models for performance. He has decades of experience developing high performance numerical software for large scale, distributed memory systems with multicore processors and GPU accelerators. Recently, Piotr served a co-PI for the ECP xSDK project whose main goal was to improve access to the world-class software on the Exascale machines.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">Piotr Luszczek is a Staff Scientist at MIT Lincoln Lab and a Research Associate Professor at the Innovative Computing Laboratory in the University of Tennessee. He earned his MSc in Computer Science from AGH University of Science and Technology in Krakow, Poland, and his PhD in Computer Science from the University of Tennessee Knoxville. His research interests include numerical linear algebra for high-performance computing, automated performance engineering for hardware accelerators, and stochastic models for performance. He has decades of experience developing high performance numerical software for large scale, distributed memory systems with multicore processors and GPU accelerators. 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