Addressing a limited power budget is a prerequisite for maintaining the growth of computer system performance into and beyond the exascale. Two technologies with the potential to help solve this problem include general-purpose programming on graphics processors and fast non-volatile memories. Combining these technologies could yield devices capable of extreme-scale computation at lower power. The goal of this project is to design a simulator supporting a hybrid memory system, containing both dynamic random-access memory (DRAM) and phase-change random-access memory (PCRAM), to replace the graphics global memory. Because of the proprietary nature of graphics hardware and the relative immaturity of phase-change memory, it is necessary to develop an appropriate simulation framework to conduct further research. In this work, GPGPU-Sim and a modified version of DRAMSim2 are combined in the design of a hybrid simulator named GPUHM-Sim. The design, implementation and validation of GPUHM-Sim are the primary contributions of this work.<\/p>\n","protected":false},"excerpt":{"rendered":"
Addressing a limited power budget is a prerequisite for maintaining the growth of computer system performance into and beyond the exascale. Two technologies with the potential to help solve this problem include general-purpose programming on graphics processors and fast non-volatile memories. Combining these technologies could yield devices capable of extreme-scale computation at lower power. The […]<\/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":[1782,14,273,20,234,953,379,1006,931,390],"class_list":["post-7535","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-computer-science","tag-cuda","tag-memory-model","tag-nvidia","tag-nvidia-geforce-gtx-280","tag-nvidia-geforce-gtx-470","tag-nvidia-geforce-gtx-480","tag-tesla-c2070","tag-tesla-m2050","tag-thesis"],"views":2918,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7535","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=7535"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7535\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=7535"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=7535"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=7535"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}