{"action":"created","issue":{"url":"https://api.github.com/repos/dmlc/mxnet/issues/4062","repository_url":"https://api.github.com/repos/dmlc/mxnet","labels_url":"https://api.github.com/repos/dmlc/mxnet/issues/4062/labels{/name}","comments_url":"https://api.github.com/repos/dmlc/mxnet/issues/4062/comments","events_url":"https://api.github.com/repos/dmlc/mxnet/issues/4062/events","html_url":"https://github.com/dmlc/mxnet/issues/4062","id":193019847,"number":4062,"title":"what kind of GPU you are using ?","user":{"login":"kernel8liang","id":4519261,"avatar_url":"https://avatars.githubusercontent.com/u/4519261?v=3","gravatar_id":"","url":"https://api.github.com/users/kernel8liang","html_url":"https://github.com/kernel8liang","followers_url":"https://api.github.com/users/kernel8liang/followers","following_url":"https://api.github.com/users/kernel8liang/following{/other_user}","gists_url":"https://api.github.com/users/kernel8liang/gists{/gist_id}","starred_url":"https://api.github.com/users/kernel8liang/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/kernel8liang/subscriptions","organizations_url":"https://api.github.com/users/kernel8liang/orgs","repos_url":"https://api.github.com/users/kernel8liang/repos","events_url":"https://api.github.com/users/kernel8liang/events{/privacy}","received_events_url":"https://api.github.com/users/kernel8liang/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":7,"created_at":"2016-12-02T02:44:55Z","updated_at":"2016-12-02T10:59:46Z","closed_at":"2016-12-02T10:59:46Z","body":"@mli \r\ntest with bandwidth tools measure.py\r\n\r\n```\r\npython measure.py --kv-store device --gpus 0,1 --network resnet --depth 200\r\nINFO:root:Namespace(batch_size=128, data_shape='128,3,224,224', depth=200, disp_batches=1, gpus='0,1', kv_store='device', network='resnet', num_batches=5, num_classes=1000, optimizer='None', test_results=1)\r\nINFO:root:/home/deepinsight/liang/workspace/mxnet/tools/bandwidth/./ResNet\r\nINFO:root:num of arrays = 205, total size = 257.991328 MB\r\nINFO:root:iter 1, 0.113931 sec, 2.264454 GB/sec per gpu, error 0.000000\r\nINFO:root:iter 2, 0.113200 sec, 2.279076 GB/sec per gpu, error 0.000000\r\nINFO:root:iter 3, 0.115689 sec, 2.230041 GB/sec per gpu, error 0.000000\r\nINFO:root:iter 4, 0.110764 sec, 2.329203 GB/sec per gpu, error 0.000000\r\nINFO:root:iter 5, 0.110690 sec, 2.330758 GB/sec per gpu, error 0.000000\r\n```\r\nwhich is far away from your perfemence:\r\n\r\n```\r\n/mxnet/tools/bandwidth $ python measure.py --kv-store device --gpus 0,1 --network resnet --depth 200\r\nINFO:root:Namespace(batch_size=128, data_shape='128,3,224,224', depth=200, disp_batches=1, gpus='0,1', kv_store='device', network='resnet', num_batches=5, num_classes=1000, optimizer='None', test_results=1)\r\nINFO:root:num of arrays = 205, total size = 257.991328 MB\r\nINFO:root:iter 1, 0.023242 sec, 11.100222 GB/sec per gpu, error 0.000000\r\nINFO:root:iter 2, 0.023106 sec, 11.165508 GB/sec per gpu, error 0.000000\r\nINFO:root:iter 3, 0.023218 sec, 11.111735 GB/sec per gpu, error 0.000000\r\nINFO:root:iter 4, 0.023193 sec, 11.123614 GB/sec per gpu, error 0.000000\r\nINFO:root:iter 5, 0.023089 sec, 11.173694 GB/sec per gpu, error 0.000000\r\n```\r\n\r\ntest with cpu E5-2660 v4 * 2 ,  m40 * 8, mem 256G, using cuda 7.5"},"comment":{"url":"https://api.github.com/repos/dmlc/mxnet/issues/comments/264429049","html_url":"https://github.com/dmlc/mxnet/issues/4062#issuecomment-264429049","issue_url":"https://api.github.com/repos/dmlc/mxnet/issues/4062","id":264429049,"user":{"login":"kernel8liang","id":4519261,"avatar_url":"https://avatars.githubusercontent.com/u/4519261?v=3","gravatar_id":"","url":"https://api.github.com/users/kernel8liang","html_url":"https://github.com/kernel8liang","followers_url":"https://api.github.com/users/kernel8liang/followers","following_url":"https://api.github.com/users/kernel8liang/following{/other_user}","gists_url":"https://api.github.com/users/kernel8liang/gists{/gist_id}","starred_url":"https://api.github.com/users/kernel8liang/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/kernel8liang/subscriptions","organizations_url":"https://api.github.com/users/kernel8liang/orgs","repos_url":"https://api.github.com/users/kernel8liang/repos","events_url":"https://api.github.com/users/kernel8liang/events{/privacy}","received_events_url":"https://api.github.com/users/kernel8liang/received_events","type":"User","site_admin":false},"created_at":"2016-12-02T10:59:46Z","updated_at":"2016-12-02T10:59:46Z","body":"I test with the newest code, get most the same performance with your's.\r\n\r\n```\r\npython measure.py --kv-store device --gpus 0,1 --network resnet --depth 200\r\nINFO:root:Namespace(batch_size=128, data_shape='128,3,224,224', depth=200, disp_batches=1, gpus='0,1', kv_store='device', network='resnet', num_batches=5, num_classes=1000, optimizer='None', test_results=1)\r\nINFO:root:num of arrays = 205, total size = 257.991328 MB\r\nINFO:root:iter 1, 0.026104 sec, 9.883221 GB/sec per gpu, error 0.000000\r\nINFO:root:iter 2, 0.025470 sec, 10.129216 GB/sec per gpu, error 0.000000\r\nINFO:root:iter 3, 0.025263 sec, 10.212192 GB/sec per gpu, error 0.000000\r\nINFO:root:iter 4, 0.025404 sec, 10.155549 GB/sec per gpu, error 0.000000\r\nINFO:root:iter 5, 0.025327 sec, 10.186428 GB/sec per gpu, error 0.000000\r\n```\r\n\r\nabout\r\n```\r\nLnkSta: Speed 2.5GT/s, Width x16\r\n```\r\n\r\nvendor tell me, when pci-e bus is idle, set the bus to 1x.\r\n\r\n \r\nthanks."}}
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