{"id":4961,"date":"2011-08-02T17:13:38","date_gmt":"2011-08-02T14:13:38","guid":{"rendered":"http:\/\/hgpu.org\/?p=4961"},"modified":"2011-08-02T17:13:38","modified_gmt":"2011-08-02T14:13:38","slug":"cost-effective-low-power-graphics-processing-unit-for-handheld-devices","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=4961","title":{"rendered":"Cost-effective low-power graphics processing unit for handheld devices"},"content":{"rendered":"<p>Cost-effective handheld graphics processing units are discussed in the aspects of performance, memory bandwidth, power, and area requirements. The proposed RamP architecture has special features of cost-effective low-power arithmetic units, memory bandwidth reduction, and dynamic power management schemes for handheld GPUs. The detailed design of RamP- VI is explained as an example of the RamP architecture. It adopts logarithmic arithmetic for power and area efficiency, and has a triple- domain power management scheme to minimize power consumption at a given performance level. The proposed GPU shows peak performance of 141 Mvertices\/s and 52.4 mW power consumption when it operates at 60 frames\/s. It shows 17.5 percent performance improvement and 50.5 percent power reduction compared to the latest work.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Cost-effective handheld graphics processing units are discussed in the aspects of performance, memory bandwidth, power, and area requirements. The proposed RamP architecture has special features of cost-effective low-power arithmetic units, memory bandwidth reduction, and dynamic power management schemes for handheld GPUs. The detailed design of RamP- VI is explained as an example of the RamP [&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":[11,3],"tags":[1782,633,182,31],"class_list":["post-4961","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-paper","tag-computer-science","tag-hardware-architecture","tag-opengl","tag-review"],"views":2313,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4961","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=4961"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4961\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4961"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4961"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4961"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}