{"id":6830,"date":"2012-01-04T21:11:24","date_gmt":"2012-01-04T19:11:24","guid":{"rendered":"http:\/\/hgpu.org\/?p=6830"},"modified":"2012-01-04T21:11:24","modified_gmt":"2012-01-04T19:11:24","slug":"efficient-mapping-of-the-training-of-convolutional-neural-networks-to-a-cuda-based-cluster","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=6830","title":{"rendered":"Efficient mapping of the training of Convolutional Neural Networks to a CUDA-based cluster"},"content":{"rendered":"<p>We propose a method to parallelize the training of a convolutional neural network by using a CUDA-based cluster. We attain a substantial increase in the performance of the algorithm itself. We research the feasibility of using batch versus online mode training and provide a performance comparison between them. Furthermore, we propose an implementation of an alternative algorithm to compute local gradients which increases the level of parallelism. To conclude, we give a set of best practices for implementing Convolutional Neural Networks on the cluster.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We propose a method to parallelize the training of a convolutional neural network by using a CUDA-based cluster. We attain a substantial increase in the performance of the algorithm itself. We research the feasibility of using batch versus online mode training and provide a performance comparison between them. Furthermore, we propose an implementation of an [&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":[36,11,89,3],"tags":[1787,330,1782,14,106,34,20,1091,67],"class_list":["post-6830","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-computer-science","category-nvidia-cuda","category-paper","tag-algorithms","tag-cnn","tag-computer-science","tag-cuda","tag-gpu-cluster","tag-neural-networks","tag-nvidia","tag-nvidia-geforce-gtx-570","tag-performance"],"views":2496,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6830","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=6830"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6830\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6830"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=6830"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=6830"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}