This is the second volume of Morgan Kaufmann’s GPU Computing Gems, offering an all-new set of insights, ideas, and practical ";hands-on"; skills from researchers and developers worldwide. Each chapter gives you a window into the work being performed across a variety of application domains, and the opportunity to witness the impact of parallel GPU computing on the efficiency of scientific research. GPU Computing Gems: Jade Edition showcases the latest research solutions with GPGPU and CUDA, including: Improving memory access patterns for cellular automata using CUDA; Large-scale gas turbine simulations on GPU clusters; Identifying and mitigating credit risk using large-scale economic capital simulations; GPU-powered MATLAB acceleration with Jacket; Biologically-inspired machine vision; An efficient CUDA algorithm for the maximum network flow problem; 30 more chapters of innovative GPU computing ideas, written to be accessible to researchers from any industry. GPU Computing Gems: Jade Edition contains 100% new material covering a variety of application domains: algorithms and data structures, engineering, interactive physics for games, computational finance, and programming tools.<\/p>\n","protected":false},"excerpt":{"rendered":"
This is the second volume of Morgan Kaufmann’s GPU Computing Gems, offering an all-new set of insights, ideas, and practical ";hands-on"; skills from researchers and developers worldwide. Each chapter gives you a window into the work being performed across a variety of application domains, and the opportunity to witness the impact of parallel GPU computing […]<\/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":[36,11,73,89,576,104,3],"tags":[1787,105,774,592,1782,1791,14,1804,1795,539,106,20],"class_list":["post-5895","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-computer-science","category-computer-vision","category-nvidia-cuda","category-finance","category-fluid-dynamics","category-paper","tag-algorithms","tag-book","tag-cellular-automata","tag-computational-finance","tag-computer-science","tag-computer-vision","tag-cuda","tag-finance","tag-fluid-dynamics","tag-games","tag-gpu-cluster","tag-nvidia"],"views":6365,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5895","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=5895"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5895\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5895"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5895"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5895"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}