As we approach the end of conventional technology scaling, computer architects are forced to incorporate specialized and heterogeneous accelerators into general-purpose processors for greater energy efficiency. Among the prominent accelerators that have recently become more popular are data-parallel processing units, such as classic vector units, SIMD units, and graphics processing units (GPUs). Surveying a wide range of data-parallel architectures and their parallel programming models and compilers reveals an opportunity to construct a new data-parallel machine that is highly performant and efficient, yet a favorable compiler target that maintains the same level of programmability as the others. In this thesis, I present the Hwacha decoupled vector-fetch architecture as the basis of a new data-parallel machine. I reason through the design decisions while describing its programming model, microarchitecture, and LLVM-based scalarizing compiler that efficiently maps OpenCL kernels to the architecture. The Hwacha vector unit is implemented in Chisel as an accelerator attached to a RISC-V Rocket control processor within the open-source Rocket Chip SoC generator. Using complete VLSI implementations of Hwacha, including a cache-coherent memory hierarchy in a commercial 28 nm process and simulated LPDDR3 DRAM modules, I quantify the area, performance, and energy consumption of the Hwacha accelerator. These numbers are then validated against an ARM Mali-T628 MP6 GPU, also built in a 28 nm process, using a set of OpenCL microbenchmarks compiled from the same source code with our custom compiler and ARM’s stock OpenCL compiler.<\/p>\n","protected":false},"excerpt":{"rendered":"
As we approach the end of conventional technology scaling, computer architects are forced to incorporate specialized and heterogeneous accelerators into general-purpose processors for greater energy efficiency. Among the prominent accelerators that have recently become more popular are data-parallel processing units, such as classic vector units, SIMD units, and graphics processing units (GPUs). Surveying a wide […]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"closed","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":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[11,89,90,3],"tags":[1782,14,534,452,1814,1793,67,193,1829,390],"class_list":["post-15974","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-opencl","category-paper","tag-computer-science","tag-cuda","tag-electronic-design-automation","tag-heterogeneous-systems","tag-llvm","tag-opencl","tag-performance","tag-ptx","tag-soc","tag-thesis"],"views":2093,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/15974","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=15974"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/15974\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=15974"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=15974"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=15974"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}