{"id":5221,"date":"2011-08-19T19:40:36","date_gmt":"2011-08-19T16:40:36","guid":{"rendered":"http:\/\/hgpu.org\/?p=5221"},"modified":"2011-08-19T19:40:36","modified_gmt":"2011-08-19T16:40:36","slug":"a-cluster-for-cs-education-in-the-manycore-era","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=5221","title":{"rendered":"A cluster for CS education in the manycore era"},"content":{"rendered":"<p>Traditional Beowulf clusters have been homogeneous platforms for distributed-memory MIMD parallelism. However, the shift to multicore architectures has made shared-memory MIMD parallelism increasingly important, and inexpensive manycore GPGPUs have revived SIMD parallelism. This paper presents a case study in designing and building a heterogeneous cluster as a learning platform for tera-scale distributed- and shared-memory MIMD parallelism, and GPGPU parallelism.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Traditional Beowulf clusters have been homogeneous platforms for distributed-memory MIMD parallelism. However, the shift to multicore architectures has made shared-memory MIMD parallelism increasingly important, and inexpensive manycore GPGPUs have revived SIMD parallelism. This paper presents a case study in designing and building a heterogeneous cluster as a learning platform for tera-scale distributed- and shared-memory MIMD [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","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":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[11,89,90,3],"tags":[7,455,1782,14,20,1793,252,680,67],"class_list":["post-5221","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-opencl","category-paper","tag-ati","tag-ati-radeon-hd-5870","tag-computer-science","tag-cuda","tag-nvidia","tag-opencl","tag-openmp","tag-openmpi","tag-performance"],"views":6213,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5221","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=5221"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5221\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5221"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5221"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5221"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}