Multi-core platforms have proven themselves able to accelerate numerous HPC applications. But programming data-intensive applications on such platforms is a hard, and not yet solved, problem. Not only do modern processors favor compute-intensive code, they also have diverse architectures and incompatible programming models. And even after making a difficult platform choice, extensive programming effort must be invested with an uncertain performance outcome. By taking the plunge on an irregular, data-intensive application, we present an evaluation of three platform types, namely the generic multi-core CPU, the STI Cell\/B.E., and the GPU. We evaluate these platforms in terms of application performance, programming effort and cost. Although we do not select a clear winner, we do provide a list of guidelines to assist in platform choice and development of similar data-intensive applications.<\/p>\n","protected":false},"excerpt":{"rendered":"
Multi-core platforms have proven themselves able to accelerate numerous HPC applications. But programming data-intensive applications on such platforms is a hard, and not yet solved, problem. Not only do modern processors favor compute-intensive code, they also have diverse architectures and incompatible programming models. And even after making a difficult platform choice, extensive programming effort must […]<\/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":[36,11,89,3],"tags":[1787,545,1782,238,14,20,183,234,70,199],"class_list":["post-2738","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-computer-science","category-nvidia-cuda","category-paper","tag-algorithms","tag-cell-processor","tag-computer-science","tag-cublas","tag-cuda","tag-nvidia","tag-nvidia-geforce-8800-gtx","tag-nvidia-geforce-gtx-280","tag-programming-techniques","tag-tesla-c1060"],"views":1834,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2738","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=2738"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2738\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2738"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2738"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2738"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}