{"action":"created","issue":{"url":"https://api.github.com/repos/CNugteren/CLBlast/issues/116","repository_url":"https://api.github.com/repos/CNugteren/CLBlast","labels_url":"https://api.github.com/repos/CNugteren/CLBlast/issues/116/labels{/name}","comments_url":"https://api.github.com/repos/CNugteren/CLBlast/issues/116/comments","events_url":"https://api.github.com/repos/CNugteren/CLBlast/issues/116/events","html_url":"https://github.com/CNugteren/CLBlast/issues/116","id":183211905,"number":116,"title":"Error in tuning results","user":{"login":"MigMuc","id":22576608,"avatar_url":"https://avatars.githubusercontent.com/u/22576608?v=3","gravatar_id":"","url":"https://api.github.com/users/MigMuc","html_url":"https://github.com/MigMuc","followers_url":"https://api.github.com/users/MigMuc/followers","following_url":"https://api.github.com/users/MigMuc/following{/other_user}","gists_url":"https://api.github.com/users/MigMuc/gists{/gist_id}","starred_url":"https://api.github.com/users/MigMuc/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/MigMuc/subscriptions","organizations_url":"https://api.github.com/users/MigMuc/orgs","repos_url":"https://api.github.com/users/MigMuc/repos","events_url":"https://api.github.com/users/MigMuc/events{/privacy}","received_events_url":"https://api.github.com/users/MigMuc/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":3,"created_at":"2016-10-15T14:17:35Z","updated_at":"2016-10-16T09:54:57Z","closed_at":null,"body":"I started to tune my GPU device (Tonga) as described in the README. Then  I started the python script which then gives an error (division by 0). So I found that there is one *.json file which has a timing result of 0.000.\r\n`{\r\n100       \"kernel\": \"XgemvFast\",\r\n101       \"time\": 0.000,\r\n102       \"parameters\": {\"WGS2\": 64,\"WPT2\": 4,\"VW2\": 4,\"PRECISION\": 6464}\r\n103     }, `\r\n\r\nLooking at other timings I see a bunch of results with timings close to 0.000 (order of nanoseconds).\r\n`{\r\n105       \"kernel\": \"XgemvFast\",\r\n106       \"time\": 0.003,\r\n107       \"parameters\": {\"WGS2\": 128,\"WPT2\": 1,\"VW2\": 1,\"PRECISION\": 6464}\r\n108     }, `\r\n\r\nI think this is not realistic.\r\n\r\n\r\n"},"comment":{"url":"https://api.github.com/repos/CNugteren/CLBlast/issues/comments/254037700","html_url":"https://github.com/CNugteren/CLBlast/issues/116#issuecomment-254037700","issue_url":"https://api.github.com/repos/CNugteren/CLBlast/issues/116","id":254037700,"user":{"login":"CNugteren","id":1162108,"avatar_url":"https://avatars.githubusercontent.com/u/1162108?v=3","gravatar_id":"","url":"https://api.github.com/users/CNugteren","html_url":"https://github.com/CNugteren","followers_url":"https://api.github.com/users/CNugteren/followers","following_url":"https://api.github.com/users/CNugteren/following{/other_user}","gists_url":"https://api.github.com/users/CNugteren/gists{/gist_id}","starred_url":"https://api.github.com/users/CNugteren/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/CNugteren/subscriptions","organizations_url":"https://api.github.com/users/CNugteren/orgs","repos_url":"https://api.github.com/users/CNugteren/repos","events_url":"https://api.github.com/users/CNugteren/events{/privacy}","received_events_url":"https://api.github.com/users/CNugteren/received_events","type":"User","site_admin":false},"created_at":"2016-10-16T09:54:57Z","updated_at":"2016-10-16T09:54:57Z","body":"Thanks for the input. Some observations:\r\n\r\n* The 0.0 ms (or close to zero) is clearly an error since the attained throughput is way beyond what you would expect on any device.\r\n* It could be that the kernel crashed or did not run at all. However, then CLTune should give a warning stating that the results are incorrect. Apparently it does not, perhaps there is a bug in results-checking? I will verify this.\r\n* The problem is across all 3 flavours of the GEMV kernels: Xgemv, XgemvFast, and XgemvFastRot. So it doesn't seem to be kernel-specific. However of course these kernels share some common code.\r\n\r\nIs this only the case for double-complex precision (6464)? Perhaps the compiler can't handle some of the parts of the kernel for given configurations if it becomes too complicated?\r\n\r\nBy the way, this is on the `development` branch, right?"}}
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