This thesis deals with code generation for parallel applications on emerging platforms, in particular FPGA and GPU-based platforms. These platforms expose a large design space, throughout which performance is affected by significant architectural idiosyncrasies. In this context, generating efficient code is a global optimization problem. The code generation methods described in this thesis apply to applications which expose a flexible parallel structure that is not bound to the target platform. The application is restructured in a way which can be intuitively visualized as Origami (the Japanese art of paper folding). The thesis makes three significant contributions: (1) It provides code generation methods starting from a general stream processing language (StreamIt) for both FPGA and GPU platforms. (2) It describes how the code generation methods can be extended beyond streaming applications to finer-grained parallel computation. On FPGAs, this is illustrated by a method that generates configurable floating-point SIMD coprocessors for vectorizable code. On GPUs, the method is extended to applications which expose fine-grained parallel code accompanied by a significant amount of read sharing. (3) It shows how these methods can be used on a platform which consists of multiple GPU devices connected to a host CPU. The methods can be applied to a broad range of applications. They go beyond mapping and provide tightly integrated code generation tools that handle together high-level mapping, code rewriting, optimizations and modular compilation. These methods target FPGA and GPU platforms without requiring user-added annotations. The results indicate the efficiency of the methods described.<\/p>\n","protected":false},"excerpt":{"rendered":"
This thesis deals with code generation for parallel applications on emerging platforms, in particular FPGA and GPU-based platforms. These platforms expose a large design space, throughout which performance is affected by significant architectural idiosyncrasies. In this context, generating efficient code is a global optimization problem. The code generation methods described in this thesis apply to […]<\/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":[215,1782,14,377,20,183,298,244,390],"class_list":["post-7365","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-fpga","tag-nvidia","tag-nvidia-geforce-8800-gtx","tag-optimization","tag-tesla-s1070","tag-thesis"],"views":2524,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7365","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=7365"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7365\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=7365"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=7365"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=7365"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}