{"id":6582,"date":"2011-12-14T17:31:49","date_gmt":"2011-12-14T15:31:49","guid":{"rendered":"http:\/\/hgpu.org\/?p=6582"},"modified":"2011-12-14T17:31:49","modified_gmt":"2011-12-14T15:31:49","slug":"a-novel-multi-gpu-neural-simulator","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=6582","title":{"rendered":"A Novel Multi-GPU Neural Simulator"},"content":{"rendered":"<p>Between the biophysical and behavioral studies of the brain lies computational neuroscience. The goal of which, among other things, is to help bridge the gap in our knowledge and provide alternative or complimentary theories to other neurological studies. As more information is provided and more complex theories are developed, the size and computational cost of neural models continues to increase. This is an obvious impediment to the field and something that developers are constantly attempting to overcome. Presented here is a unique simulator design aimed at leveraging advances in hardware for the simulation of biologically realistic neural models. This proof-of-concept design offers an example of a high-performance environment that utilizes multiple general purpose graphical processing units in a novel configuration. The result is a scalable system that offers the promise of both performance and biophysical faithfulness.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Between the biophysical and behavioral studies of the brain lies computational neuroscience. The goal of which, among other things, is to help bridge the gap in our knowledge and provide alternative or complimentary theories to other neurological studies. As more information is provided and more complex theories are developed, the size and computational cost of [&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":[10,89,3],"tags":[1781,29,14,506,20,379],"class_list":["post-6582","post","type-post","status-publish","format-standard","hentry","category-biology","category-nvidia-cuda","category-paper","tag-biology","tag-biophysics","tag-cuda","tag-neuroscience","tag-nvidia","tag-nvidia-geforce-gtx-480"],"views":2335,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6582","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=6582"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6582\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6582"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=6582"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=6582"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}