{"id":128,"date":"2014-03-18T14:37:13","date_gmt":"2014-03-18T13:37:13","guid":{"rendered":"https:\/\/site.uit.no\/arcticgreen\/?page_id=128"},"modified":"2025-09-01T15:36:05","modified_gmt":"2025-09-01T13:36:05","slug":"preapp-productivity-and-energy-efficiency-through-abstraction-based-parallel-programming","status":"publish","type":"page","link":"https:\/\/site.uit.no\/arcticgreen\/projects\/preapp-productivity-and-energy-efficiency-through-abstraction-based-parallel-programming\/","title":{"rendered":"PREAPP &#8211; PRoductivity and Energy-efficiency through Abstraction-based Parallel Programming"},"content":{"rendered":"<p>In today&#8217;s exponential world of digital data, big data services have made the power consumption the lion&#8217;s share of the total cost. For instance, Google data centers consume almost 260 MW, about a quarter of the output of a nuclear power plant, enough to power 200 000 homes. Energy efficiency is therefore considered a major criterion for &#8220;sustainable&#8221; computing systems and services over the data deluge. However, energy-efficient computing systems make parallel programming even more complex and thereby less robust due to requirements of massive parallelism, heterogeneity and data locality.<\/p>\n<p>The PREAPP project aims to devise novel programming models that will form foundations for a paradigm shift from energy &#8220;blind&#8221; to energy &#8220;aware&#8221; software development. The new models will enable one order of magnitude improvement in energy efficiency in comparison with today&#8217;s multicore computing, thereby greatly advancing green computing and sustainable services. The new models will facilitate unprecedented productivity for implementing scientific big data applications that run effectively on large-scale high-performance computing (HPC) platforms, which are based on cutting-edge manycore architectures. The threshold of adopting large-scale parallel computing will thus be considerably lowered for a large number of computational scientists in several disciplines.<\/p>\n<p><a href=\"https:\/\/prosjektbanken.forskningsradet.no\/en\/project\/FORISS\/231746?Kilde=FORISS&amp;distribution=Ar&amp;chart=bar&amp;calcType=funding&amp;Sprak=no&amp;sortBy=date&amp;sortOrder=desc&amp;resultCount=30&amp;offset=360&amp;ProgAkt.3=FRINATEK-Fri+prosj.st.+mat.%2Cnaturv.%2Ctek&amp;source=FORISS&amp;projectId=213985\">PREAPP<\/a> is a Norwegian Independent\u00a0project (<a href=\"http:\/\/www.forskningsradet.no\/prognett-fripro\/About_FRIPRO\/1253954757377\" target=\"_blank\" rel=\"noopener\">FRIPRO<\/a>) under\u00a0<a title=\"FRIPRO Young Research Talents\" href=\"http:\/\/www.forskningsradet.no\/prognett-fripro\/Nyheter\/Funding_for_independent_projects_103_projects_awarded_NOK_607_million\/1253991363603\/p1226994096494\" target=\"_blank\" rel=\"noopener\">Young Research Talents category<\/a> (2014 &#8211; 2019) with total cost of 7.9M NOK (<a href=\"https:\/\/prosjektbanken.forskningsradet.no\/project\/FORISS\/231746\">grant n\u25e6 231746<\/a>). Norwegian prestigious funding scheme <a href=\"http:\/\/www.forskningsradet.no\/prognett-fripro\/About_FRIPRO\/1253954757377\">FRIPRO<\/a>\u00a0is designed to promote research of high scientific quality independent of research area and discipline. In the PREAPP project, the Arctic Green Computing group is the project leader.<\/p>\n<p><a href=\"http:\/\/www.forskningsradet.no\/en\/Home_page\/1177315753906\"><img decoding=\"async\" class=\"alignnone wp-image-130\" src=\"https:\/\/site.uit.no\/arcticgreen\/wp-content\/uploads\/sites\/175\/2014\/03\/rcn-300x54.jpg\" alt=\"rcn\" width=\"234\" height=\"41\" \/><\/a><\/p>\n<iframe src=\"http:\/\/www.facebook.com\/plugins\/like.php?href=https%3A%2F%2Fsite.uit.no%2Farcticgreen%2Fprojects%2Fpreapp-productivity-and-energy-efficiency-through-abstraction-based-parallel-programming%2F&amp;layout=standard&amp;show_faces=true&amp;width=450&amp;action=like&amp;colorscheme=light&amp;height=80\" scrolling=\"no\" frameborder=\"0\" style=\"border:none; overflow:hidden; width:450px; height:80px;\" allowTransparency=\"true\"><\/iframe>","protected":false},"excerpt":{"rendered":"<p>In today&#8217;s exponential world of digital data, big data services have made the power consumption the lion&#8217;s share of the total cost. For instance, Google data centers consume almost 260 MW, about a quarter of the output of a nuclear &hellip; <a href=\"https:\/\/site.uit.no\/arcticgreen\/projects\/preapp-productivity-and-energy-efficiency-through-abstraction-based-parallel-programming\/\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":308,"featured_media":0,"parent":26,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-128","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/site.uit.no\/arcticgreen\/wp-json\/wp\/v2\/pages\/128","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/site.uit.no\/arcticgreen\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/site.uit.no\/arcticgreen\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/site.uit.no\/arcticgreen\/wp-json\/wp\/v2\/users\/308"}],"replies":[{"embeddable":true,"href":"https:\/\/site.uit.no\/arcticgreen\/wp-json\/wp\/v2\/comments?post=128"}],"version-history":[{"count":3,"href":"https:\/\/site.uit.no\/arcticgreen\/wp-json\/wp\/v2\/pages\/128\/revisions"}],"predecessor-version":[{"id":1094,"href":"https:\/\/site.uit.no\/arcticgreen\/wp-json\/wp\/v2\/pages\/128\/revisions\/1094"}],"up":[{"embeddable":true,"href":"https:\/\/site.uit.no\/arcticgreen\/wp-json\/wp\/v2\/pages\/26"}],"wp:attachment":[{"href":"https:\/\/site.uit.no\/arcticgreen\/wp-json\/wp\/v2\/media?parent=128"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}