{"id":8002,"date":"2012-08-02T14:16:50","date_gmt":"2012-08-02T11:16:50","guid":{"rendered":"http:\/\/hgpu.org\/?p=8002"},"modified":"2012-08-02T14:16:50","modified_gmt":"2012-08-02T11:16:50","slug":"c-to-cellular-automata-and-execution-on-cpu-gpu-and-fpga","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=8002","title":{"rendered":"C to Cellular Automata and Execution on CPU, GPU and FPGA"},"content":{"rendered":"<p>Over the last decades Cellular Automata (CA) have become more and more present in solving general-purpose problems, but the main issue is how to map a problem to a Cellular Automata model. Special languages were developed for programming such models, but learning a new programming language is very time consuming. Furthermore software developers have to keep in mind the specific structure of Cellular Automata when designing a new algorithm. In this paper we present a method to generate Cellular Automata models from standard C code. The code is transcoded by mapping the complete algorithm written in C to a Cellular Automata model that may be compiled for CPU, GPU and even FPGA without further user interaction.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Over the last decades Cellular Automata (CA) have become more and more present in solving general-purpose problems, but the main issue is how to map a problem to a Cellular Automata model. Special languages were developed for programming such models, but learning a new programming language is very time consuming. Furthermore software developers have to [&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":[774,1782,14,377,20,974,252],"class_list":["post-8002","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-cellular-automata","tag-computer-science","tag-cuda","tag-fpga","tag-nvidia","tag-nvidia-geforce-gtx-580","tag-openmp"],"views":2993,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8002","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=8002"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8002\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8002"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8002"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8002"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}