{"id":8476,"date":"2012-11-08T23:00:56","date_gmt":"2012-11-08T21:00:56","guid":{"rendered":"http:\/\/hgpu.org\/?p=8476"},"modified":"2012-11-08T23:00:56","modified_gmt":"2012-11-08T21:00:56","slug":"reusable-opencl-fpga-infrastructure","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=8476","title":{"rendered":"Reusable OpenCL FPGA Infrastructure"},"content":{"rendered":"<p>OpenCL has emerged as a standard programming model for heterogeneous systems. Recent work combining OpenCL and FPGAs has focused on high-level synthesis. Building a complete OpenCL FPGA system requires more than just high-level synthesis. This work introduces a reusable OpenCL infrastructure for FPGAs that complements previous work and specifically targets a key architectural element &#8211; the memory interface. An Aggregating Memory Controller that aims to maximize bandwidth to external, large, high-latency, high-bandwidth memories and a template Processing Array with soft-processor and hand-coded hardware elements are designed, simulated, and implemented on an FPGA. Two micro-benchmarks were run on both the soft-processor elements and the hand-coded hardware elements to exercise the Aggregating Memory Controller. The micro-benchmarks were simulated as well as implemented in a hardware prototype. Memory bandwidth results for the system show that the external memory interface can be saturated and the high-latency can be effectively hidden using the Aggregating Memory Controller.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>OpenCL has emerged as a standard programming model for heterogeneous systems. Recent work combining OpenCL and FPGAs has focused on high-level synthesis. Building a complete OpenCL FPGA system requires more than just high-level synthesis. This work introduces a reusable OpenCL infrastructure for FPGAs that complements previous work and specifically targets a key architectural element &#8211; [&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":[11,90,3],"tags":[1782,377,452,1793,390],"class_list":["post-8476","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-opencl","category-paper","tag-computer-science","tag-fpga","tag-heterogeneous-systems","tag-opencl","tag-thesis"],"views":2952,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8476","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=8476"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8476\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8476"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8476"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8476"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}