{"id":248,"date":"2023-02-14T08:00:17","date_gmt":"2023-02-14T08:00:17","guid":{"rendered":"https:\/\/christian-engelmann.de\/?page_id=248"},"modified":"2023-02-18T01:30:56","modified_gmt":"2023-02-18T01:30:56","slug":"2011-12-extreme-scale-algorithms-and-software-institute","status":"publish","type":"page","link":"https:\/\/www.christian-engelmann.info\/?page_id=248","title":{"rendered":"2011-12: Extreme-scale Algorithms and Software Institute"},"content":{"rendered":"<p>The Extreme-scale Algorithms and Software Institute (EASI), formed by Oak Ridge National Laboratory, Sandia National Laboratories and the Universities of Illinois, Tennessee, and California Berkeley, focuses on closing the application-architecture performance gap through architecture-aware algorithms and libraries, and the supporting runtime capabilities to achieve scalable performance and resilience on heterogeneous architectures.<\/p>\n<p>Specifically, EASI aims at: (1) studying and characterize the application-architecture performance gaps that we can address in the near-term and identify architecture features that future systems may want to incorporate; (2) developing multi-precision and architecture-aware implementations of Krylov, Poisson and Helmholtz solvers, and dense factorizations for heterogeneous multi-core systems; (3) exploring new methods of algorithm resilience, and develop new algorithms with these capabilities; (4) developing runtime support for adaptable algorithms dealing with resilience, scalability, and performance; (5) demonstrating architecture-aware algorithms in full U.S. Department of Energy (DOE) applications on large-scale DOE architectures; (6) distributing the new algorithms and supporting runtime capabilities through widely used software packages; and (7) establishing a strong outreach program to disseminate results, interact with colleagues and train students and junior members of our community.<\/p>\n<h4>Solutions<\/h4>\n<ul>\n<li><a href=\"?page_id=433\">xSim: The Extreme-scale Simulator<\/a><\/li>\n<\/ul>\n<h4>Funding Sources<\/h4>\n<ul>\n<li>\n<a href=\"http:\/\/science.energy.gov\/ascr\" target=\"science.energy.gov_ascr\" rel=\"noopener\">Office of Advanced Scientific Computing Research<\/a>, Office of Science, U.S. Department of Energy<\/li>\n<\/ul>\n<h4>Participating Institutions<\/h4>\n<ul>\n<li><a href=\"http:\/\/www.ornl.gov\" target=\"www.ornl.gov\" rel=\"noopener\">Oak Ridge National Laboratory<\/a><\/li>\n<li><a href=\"http:\/\/www.sandia.gov\" target=\"www.sandia.gov\" rel=\"noopener\">Sandia National Laboratory<\/a><\/li>\n<li><a href=\"http:\/\/www.illinois.edu\" target=\"www.illinois.edu\" rel=\"noopener\">University of Illinois at Urbana-Champaign<\/a><\/li>\n<li><a href=\"http:\/\/www.berkeley.edu\" target=\"www.berkeley.edu\" rel=\"noopener\">University of California at Berkeley<\/a><\/li>\n<li><a href=\"http:\/\/www.utk.edu\" target=\"www.utk.edu\" rel=\"noopener\">University of Tennessee, Knoxville<\/a><\/li>\n<\/ul>\n<h4>Peer-reviewed Journal Publications<\/h4>\n<ol>\n<li>Christian Engelmann. <b>Scaling To A Million Cores And Beyond: Using Light-Weight Simulation to Understand The Challenges Ahead On The Road To Exascale<\/b>. <i><a href=\"http:\/\/www.elsevier.com\/locate\/fgcs\" target=\"www.elsevier.com\/locate\/fgcs\" rel=\"noopener\">Future Generation Computer Systems (FGCS)<\/a><\/i>, volume 30, number 0, pages 59-65, January 1, 2014. <a href=\"http:\/\/www.elsevier.com\" target=\"www.elsevier.com\" rel=\"noopener\">Elsevier B.V, Amsterdam, The Netherlands<\/a>. ISSN 0167-739X. DOI <a href=\"http:\/\/dx.doi.org\/10.1016\/j.future.2013.04.014\" target=\"publication\" rel=\"noopener\">10.1016\/j.future.2013.04.014<\/a>. <a href=\"javascript:showAbstract('As supercomputers scale to 1,000 PFlop\/s over the next decade, investigating the performance of parallel applications at scale on future architectures and the performance impact of different architecture choices for high-performance computing (HPC) hardware\/software co-design is crucial. This paper summarizes recent efforts in designing and implementing a novel HPC hardware\/software co-design toolkit. The presented Extreme-scale Simulator (xSim) permits running an HPC application in a controlled environment with millions of concurrent execution threads while observing its performance in a simulated extreme-scale HPC system using architectural models and virtual timing. This paper demonstrates the capabilities and usefulness of the xSim performance investigation toolkit, such as its scalability to 2^27 simulated Message Passing Interface (MPI) ranks on 960 real processor cores, the capability to evaluate the performance of different MPI collective communication algorithms, and the ability to evaluate the performance of a basic Monte Carlo application with different architectural parameters.');\"><img decoding=\"async\" src=\"images\/txt.gif\" border=\"0\" style=\"border-style:none\" height=\"10pt\" alt=\"Abstract\"><\/a> <a href=\"publications\/engelmann13scaling.pdf\" target=\"publication\" rel=\"noopener\"><img decoding=\"async\" src=\"images\/pdf.gif\" border=\"0\" style=\"border-style:none\" height=\"10pt\" alt=\"Publication\"><\/a> <a href=\"?page_id=55#engelmann13scaling\"><img decoding=\"async\" src=\"images\/bib.gif\" border=\"0\" style=\"border-style:none\" height=\"10pt\" alt=\"BibTeX Citation\"><\/a><\/li>\n<\/ol>\n<h4>Peer-reviewed Conference Publications<\/h4>\n<ol>\n<li>Christian Engelmann. <b>Investigating Operating System Noise in Extreme-Scale High-Performance Computing Systems using Simulation<\/b>. In <i>Proceedings of the <a href=\"http:\/\/www.iasted.org\/conferences\/home-795.html\" target=\"www.iasted.org\/conferences\/home-795.html\" rel=\"noopener\">11th IASTED International Conference on Parallel and Distributed Computing and Networks (PDCN) 2013<\/a><\/i>, Innsbruck, Austria, February 11-13, 2013. <a href=\"http:\/\/www.actapress.com\" target=\"www.actapress.com\" rel=\"noopener\">ACTA Press, Calgary, AB, Canada<\/a>. ISBN 978-0-88986-943-1. DOI <a href=\"http:\/\/dx.doi.org\/10.2316\/P.2013.795-010\" target=\"publication\" rel=\"noopener\">10.2316\/P.2013.795-010<\/a>. <a href=\"javascript:showAbstract('Hardware\/software co-design for future-generation high-performance computing (HPC) systems aims at closing the gap between the peak capabilities of the hardware and the performance realized by applications (application-architecture performance gap). Performance profiling of architectures and applications is a crucial part of this iterative process. The work in this paper focuses on operating system (OS) noise as an additional factor to be considered for co-design. It represents the first step in including OS noise in HPC hardware\/software co-design by adding a noise injection feature to an existing simulation-based co-design toolkit. It reuses an existing abstraction for OS noise with frequency (periodic recurrence) and period (duration of each occurrence) to enhance the processor model of the Extreme-scale Simulator (xSim) with synchronized and random OS noise simulation. The results demonstrate this capability by evaluating the impact of OS noise on MPI_Bcast() and MPI_Reduce() in a simulated future-generation HPC system with 2,097,152 compute nodes.');\"><img decoding=\"async\" src=\"images\/txt.gif\" border=\"0\" style=\"border-style:none\" height=\"10pt\" alt=\"Abstract\"><\/a> <a href=\"publications\/engelmann13investigating.pdf\" target=\"publication\" rel=\"noopener\"><img decoding=\"async\" src=\"images\/pdf.gif\" border=\"0\" style=\"border-style:none\" height=\"10pt\" alt=\"Publication\"><\/a> <a href=\"publications\/engelmann13investigating.ppt.pdf\" target=\"publication\" rel=\"noopener\"><img decoding=\"async\" src=\"images\/ppt.gif\" border=\"0\" style=\"border-style:none\" height=\"10pt\" alt=\"Presentation\"><\/a> <a href=\"?page_id=55#engelmann13investigating\"><img decoding=\"async\" src=\"images\/bib.gif\" border=\"0\" style=\"border-style:none\" height=\"10pt\" alt=\"BibTeX Citation\"><\/a><\/li>\n<\/ol>\n<h4>Talks and Lectures<\/h4>\n<ol>\n<li>Christian Engelmann. <b>Scaling To A Million Cores And Beyond: A Basic Understanding Of The Challenges Ahead On The Road To Exascale<\/b>. Invited talk at the <a href=\"http:\/\/researcher.ibm.com\/researcher\/view_page.php?id=2580\" target=\"researcher.ibm.com\/researcher\/view_page.php?id=2580\" rel=\"noopener\">1st International Workshop on Extreme Scale Parallel Architectures and Systems (ESPAS) 2012<\/a>, in conjunction with the <a href=\"http:\/\/www.hipeac.net\/conference\/paris\" target=\"www.hipeac.net\/conference\/paris\" rel=\"noopener\">7th International Conference on High-Performance and Embedded Architectures and Compilers (HiPEAC) 2012<\/a>, Paris France, January 24, 2012. <a href=\"javascript:showAbstract('On the road toward multi-petascale and exascale HPC, the trend in architecture goes clearly in only one direction. HPC systems will dramatically scale up in compute node and processor core counts. By 2020, an exascale system may have up to 1,000,000 compute nodes with 1,000 cores per node. The substantial growth in concurrency causes parallel application scalability issues due to sequential application parts, synchronizing communication, and other bottlenecks. Investigating parallel algorithm performance properties at this scale and with these architectural properties for HPC hardware\/software co-design is crucial to enable extreme-scale computing. The presented work utilizes the Extreme-scale Simulator (xSim) performance investigation toolkit to identify the scaling characteristics of a simple Monte Carlo algorithm from 1 to 16 million MPI processes on different multi-core architecture choices. The results show the limitations of strong scaling and the negative impact of employing more but less powerful cores for energy savings.');\"><img decoding=\"async\" src=\"images\/txt.gif\" border=\"0\" style=\"border-style:none\" height=\"10pt\" alt=\"Abstract\"><\/a> <a href=\"publications\/engelmann12scaling.ppt.pdf\" target=\"publication\" rel=\"noopener\"><img decoding=\"async\" src=\"images\/ppt.gif\" border=\"0\" style=\"border-style:none\" height=\"10pt\" alt=\"Presentation\"><\/a> <a href=\"?page_id=55#engelmann12scaling\"><img decoding=\"async\" src=\"images\/bib.gif\" border=\"0\" style=\"border-style:none\" height=\"10pt\" alt=\"BibTeX Citation\"><\/a><\/li>\n<\/ol>\n<p><em><small>Symbols: <img decoding=\"async\" style=\"border-style: none;\" src=\"images\/txt.gif\" border=\"0\" alt=\"Abstract\" height=\"10pt\"> Abstract, <img decoding=\"async\" style=\"border-style: none;\" src=\"images\/pdf.gif\" border=\"0\" alt=\"Publication\" height=\"10pt\"> Publication, <img decoding=\"async\" style=\"border-style: none;\" src=\"images\/ppt.gif\" border=\"0\" alt=\"Presentation\" height=\"10pt\"> Presentation, <img decoding=\"async\" style=\"border-style: none;\" src=\"images\/bib.gif\" border=\"0\" alt=\"BibTeX Citation\" height=\"10pt\"> BibTeX Citation<\/small><\/em><\/p>\n<p><script language=\"JavaScript\">\nfunction showAbstract (text) {\n  var width  = 400;\n  var height = 400;\n  var left   = (screen.width  - width ) \/ 2;\n  var top    = (screen.height - height) \/ 2;\n  var win    = window.open('',\n                           'Abstract',\n                           'width='  + width  + ', ' + \n                           'height=' + height + ', ' +\n                           'left='   + left   + ', ' +\n                           'top='    + top    + ', ' +\n                           'toolbar=no, '     +\n                           'location=no, '    +\n                           'directories=no, ' +\n                           'status=no, '      +\n                           'menubar=no, '     +\n                           'copyhistory=no, ' +\n                           'scrollbars=yes, ' +\n                           'resizable=yes')\n  win.document.write(text);\n  win.document.close();\n}\n<\/script><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Extreme-scale Algorithms and Software Institute (EASI), formed by Oak Ridge National Laboratory, Sandia National Laboratories and the Universities of Illinois, Tennessee, and California Berkeley, focuses on closing the application-architecture performance gap through architecture-aware algorithms and libraries, and the supporting runtime capabilities to achieve scalable performance and resilience on heterogeneous architectures. Specifically, EASI aims at:&hellip;&nbsp;<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":145,"menu_order":24,"comment_status":"closed","ping_status":"closed","template":"","meta":{"neve_meta_sidebar":"","neve_meta_container":"","neve_meta_enable_content_width":"off","neve_meta_content_width":100,"neve_meta_title_alignment":"","neve_meta_author_avatar":"","neve_post_elements_order":"","neve_meta_disable_header":"","neve_meta_disable_footer":"","neve_meta_disable_title":"","footnotes":""},"class_list":["post-248","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.christian-engelmann.info\/index.php?rest_route=\/wp\/v2\/pages\/248","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.christian-engelmann.info\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.christian-engelmann.info\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.christian-engelmann.info\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.christian-engelmann.info\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=248"}],"version-history":[{"count":8,"href":"https:\/\/www.christian-engelmann.info\/index.php?rest_route=\/wp\/v2\/pages\/248\/revisions"}],"predecessor-version":[{"id":472,"href":"https:\/\/www.christian-engelmann.info\/index.php?rest_route=\/wp\/v2\/pages\/248\/revisions\/472"}],"up":[{"embeddable":true,"href":"https:\/\/www.christian-engelmann.info\/index.php?rest_route=\/wp\/v2\/pages\/145"}],"wp:attachment":[{"href":"https:\/\/www.christian-engelmann.info\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=248"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}