{"id":5568,"date":"2011-09-14T18:20:20","date_gmt":"2011-09-14T15:20:20","guid":{"rendered":"http:\/\/hgpu.org\/?p=5568"},"modified":"2011-09-14T18:20:20","modified_gmt":"2011-09-14T15:20:20","slug":"nikola-embedding-compiled-gpu-functions-in-haskell","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=5568","title":{"rendered":"Nikola: embedding compiled GPU functions in Haskell"},"content":{"rendered":"<p>We describe Nikola, a first-order language of array computations embedded in Haskell that compiles to GPUs via CUDA using a new set of type-directed techniques to support re-usable computations. Nikola automatically handles a range of low-level details for Haskell programmers, such as marshaling data to\/from the GPU, size inference for buffers, memory management, and automatic loop parallelization. Additionally, Nikola supports both compile-time and run-time code generation, making it possible for programmers to choose when and where to specialize embedded programs.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We describe Nikola, a first-order language of array computations embedded in Haskell that compiles to GPUs via CUDA using a new set of type-directed techniques to support re-usable computations. Nikola automatically handles a range of low-level details for Haskell programmers, such as marshaling data to\/from the GPU, size inference for buffers, memory management, and automatic [&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":[11,89,3],"tags":[215,1782,14,20,176,660,429],"class_list":["post-5568","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-code-generation","tag-computer-science","tag-cuda","tag-nvidia","tag-package","tag-programming-languages","tag-tesla-t10"],"views":2134,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5568","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=5568"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5568\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5568"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5568"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5568"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}