{"id":24403,"date":"2021-01-17T16:26:47","date_gmt":"2021-01-17T14:26:47","guid":{"rendered":"https:\/\/hgpu.org\/?p=24403"},"modified":"2021-01-17T16:26:47","modified_gmt":"2021-01-17T14:26:47","slug":"instruments-of-productivity-for-high-performance-computing","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=24403","title":{"rendered":"Instruments of Productivity for High Performance Computing"},"content":{"rendered":"<p>High performance computing (HPC) is now well established as the cornerstone for building and conducting software simulations in numerous scientific and industrial fields. The hardware complexity of supercomputers is steadily increasing, however, to deliver ever improved computing performance, causing the complexity of HPC application development to increase as well. As a result, the need for tools and methodologies to compensate the development complexity by reducing the costs it induces \u2014that is, the need for instruments to improve productivity in HPC development\u2014 has never been so pressing. This manuscript builds on the experience I have gathered while being involved in the design of several of such instruments of productivity for HPC, over the course of my academic career in computer science research, to study the technical choices made, the lessons learnt, and to discuss upcoming challenges and priorities.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>High performance computing (HPC) is now well established as the cornerstone for building and conducting software simulations in numerous scientific and industrial fields. The hardware complexity of supercomputers is steadily increasing, however, to deliver ever improved computing performance, causing the complexity of HPC application development to increase as well. As a result, the need for [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[11,3],"tags":[1782,1682,390],"class_list":["post-24403","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-paper","tag-computer-science","tag-hpc","tag-thesis"],"views":1714,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/24403","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=24403"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/24403\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=24403"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=24403"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=24403"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}