{"action":"created","issue":{"url":"https://api.github.com/repos/BVLC/caffe/issues/4328","repository_url":"https://api.github.com/repos/BVLC/caffe","labels_url":"https://api.github.com/repos/BVLC/caffe/issues/4328/labels{/name}","comments_url":"https://api.github.com/repos/BVLC/caffe/issues/4328/comments","events_url":"https://api.github.com/repos/BVLC/caffe/issues/4328/events","html_url":"https://github.com/BVLC/caffe/issues/4328","id":161010000,"number":4328,"title":"Sparse convolutional neural networks","user":{"login":"wenwei202","id":12142066,"avatar_url":"https://avatars.githubusercontent.com/u/12142066?v=3","gravatar_id":"","url":"https://api.github.com/users/wenwei202","html_url":"https://github.com/wenwei202","followers_url":"https://api.github.com/users/wenwei202/followers","following_url":"https://api.github.com/users/wenwei202/following{/other_user}","gists_url":"https://api.github.com/users/wenwei202/gists{/gist_id}","starred_url":"https://api.github.com/users/wenwei202/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/wenwei202/subscriptions","organizations_url":"https://api.github.com/users/wenwei202/orgs","repos_url":"https://api.github.com/users/wenwei202/repos","events_url":"https://api.github.com/users/wenwei202/events{/privacy}","received_events_url":"https://api.github.com/users/wenwei202/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/BVLC/caffe/labels/speed-up","name":"speed-up","color":"c7def8"}],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":20,"created_at":"2016-06-18T06:30:47Z","updated_at":"2016-09-01T03:44:09Z","closed_at":null,"body":"Anyone has interest to utilize the sparsity to accelerate DNNs?\r\n\r\nI am working on the fork https://github.com/wenwei202/caffe/tree/scnn and currently, on average, achieve ~5x CPU and ~3x GPU layer-wise speedups of convolutional layers in AlexNet by off-the-shelf GEMM (after ~2% top1 accuracy loss). "},"comment":{"url":"https://api.github.com/repos/BVLC/caffe/issues/comments/243968108","html_url":"https://github.com/BVLC/caffe/issues/4328#issuecomment-243968108","issue_url":"https://api.github.com/repos/BVLC/caffe/issues/4328","id":243968108,"user":{"login":"zhaishengfu","id":7630101,"avatar_url":"https://avatars.githubusercontent.com/u/7630101?v=3","gravatar_id":"","url":"https://api.github.com/users/zhaishengfu","html_url":"https://github.com/zhaishengfu","followers_url":"https://api.github.com/users/zhaishengfu/followers","following_url":"https://api.github.com/users/zhaishengfu/following{/other_user}","gists_url":"https://api.github.com/users/zhaishengfu/gists{/gist_id}","starred_url":"https://api.github.com/users/zhaishengfu/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/zhaishengfu/subscriptions","organizations_url":"https://api.github.com/users/zhaishengfu/orgs","repos_url":"https://api.github.com/users/zhaishengfu/repos","events_url":"https://api.github.com/users/zhaishengfu/events{/privacy}","received_events_url":"https://api.github.com/users/zhaishengfu/received_events","type":"User","site_admin":false},"created_at":"2016-09-01T03:44:09Z","updated_at":"2016-09-01T03:44:09Z","body":"@hiyijian the code says clearly, the xdimen and ydimen represents the column and row dimension respectively. For example, if you have A rows and ydimen is B, then you will have A/B groups and in each group you will use regularization"}}
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