{"action":"created","issue":{"url":"https://api.github.com/repos/NervanaSystems/nervanagpu/issues/3","labels_url":"https://api.github.com/repos/NervanaSystems/nervanagpu/issues/3/labels{/name}","comments_url":"https://api.github.com/repos/NervanaSystems/nervanagpu/issues/3/comments","events_url":"https://api.github.com/repos/NervanaSystems/nervanagpu/issues/3/events","html_url":"https://github.com/NervanaSystems/nervanagpu/issues/3","id":72470599,"number":3,"title":"Build conv kernels tailored to minibatch size of 32","user":{"login":"scott-gray","id":9326960,"avatar_url":"https://avatars.githubusercontent.com/u/9326960?v=3","gravatar_id":"","url":"https://api.github.com/users/scott-gray","html_url":"https://github.com/scott-gray","followers_url":"https://api.github.com/users/scott-gray/followers","following_url":"https://api.github.com/users/scott-gray/following{/other_user}","gists_url":"https://api.github.com/users/scott-gray/gists{/gist_id}","starred_url":"https://api.github.com/users/scott-gray/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/scott-gray/subscriptions","organizations_url":"https://api.github.com/users/scott-gray/orgs","repos_url":"https://api.github.com/users/scott-gray/repos","events_url":"https://api.github.com/users/scott-gray/events{/privacy}","received_events_url":"https://api.github.com/users/scott-gray/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":5,"created_at":"2015-05-01T16:38:26Z","updated_at":"2015-08-07T03:46:58Z","closed_at":null,"body":"I should be able to hit close to full utilization at this size.  Though N>=64 will give you more perf per watt."},"comment":{"url":"https://api.github.com/repos/NervanaSystems/nervanagpu/issues/comments/128582934","html_url":"https://github.com/NervanaSystems/nervanagpu/issues/3#issuecomment-128582934","issue_url":"https://api.github.com/repos/NervanaSystems/nervanagpu/issues/3","id":128582934,"user":{"login":"abangdd","id":3134990,"avatar_url":"https://avatars.githubusercontent.com/u/3134990?v=3","gravatar_id":"","url":"https://api.github.com/users/abangdd","html_url":"https://github.com/abangdd","followers_url":"https://api.github.com/users/abangdd/followers","following_url":"https://api.github.com/users/abangdd/following{/other_user}","gists_url":"https://api.github.com/users/abangdd/gists{/gist_id}","starred_url":"https://api.github.com/users/abangdd/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/abangdd/subscriptions","organizations_url":"https://api.github.com/users/abangdd/orgs","repos_url":"https://api.github.com/users/abangdd/repos","events_url":"https://api.github.com/users/abangdd/events{/privacy}","received_events_url":"https://api.github.com/users/abangdd/received_events","type":"User","site_admin":false},"created_at":"2015-08-07T03:46:58Z","updated_at":"2015-08-07T03:46:58Z","body":"thank you ekelsen，\r\n  I tried to wrap last week without succeess，the cuLaunchKernel report CUDA_ERROR_INVALID_VALUE error，since I have no methods to debug CUDA，I almost gave up\r\n  Now I will check and try your code and see where the differences are，should I got them working，I will post my code\r\n"}}