{"action":"created","issue":{"url":"https://api.github.com/repos/torch/cunn/issues/32","labels_url":"https://api.github.com/repos/torch/cunn/issues/32/labels{/name}","comments_url":"https://api.github.com/repos/torch/cunn/issues/32/comments","events_url":"https://api.github.com/repos/torch/cunn/issues/32/events","html_url":"https://github.com/torch/cunn/issues/32","id":46757667,"number":32,"title":"SpatialMaxsampling: too many resources requested for launch","user":{"login":"Atcold","id":2119355,"avatar_url":"https://avatars.githubusercontent.com/u/2119355?v=3","gravatar_id":"","url":"https://api.github.com/users/Atcold","html_url":"https://github.com/Atcold","followers_url":"https://api.github.com/users/Atcold/followers","following_url":"https://api.github.com/users/Atcold/following{/other_user}","gists_url":"https://api.github.com/users/Atcold/gists{/gist_id}","starred_url":"https://api.github.com/users/Atcold/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Atcold/subscriptions","organizations_url":"https://api.github.com/users/Atcold/orgs","repos_url":"https://api.github.com/users/Atcold/repos","events_url":"https://api.github.com/users/Atcold/events{/privacy}","received_events_url":"https://api.github.com/users/Atcold/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/torch/cunn/labels/bug","name":"bug","color":"fc2929"}],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":2,"created_at":"2014-10-24T16:36:55Z","updated_at":"2015-03-31T18:17:03Z","closed_at":null,"body":"I'm running a very tiny network (3-layer ConvNet with few tens of fiters) on a Nvidia Jetson TK1 with Ubuntu 14.04, Cuda 6.0 and the latest drivers (`R19.3.0_armhf`).\r\nIf I use the CPU, everything works fine and the feedforward step is completed in 10s of ms.\r\nIf I try to use the GPU (using `nn.SpatialConvolutionMM` and `nn.SpatialMaxPooling`), I get the following error message I do not understand:\r\n\r\n```lua\r\nerror in SpatialMaxsampling.updateOutput: too many resources requested for launch\r\n/usr/local/bin/luajit: /usr/local/share/lua/5.1/nn/SpatialMaxPooling.lua:18: aborting   \r\nstack traceback:                                                                        \r\n        [C]: in function 'SpatialMaxPooling_updateOutput'                               \r\n        /usr/local/share/lua/5.1/nn/SpatialMaxPooling.lua:18: in function 'updateOutput'\r\n        /usr/local/share/lua/5.1/nn/Sequential.lua:37: in function 'forward'            \r\n        ./src/profileNet.lua:32: in function 'time'                                     \r\n        general-profiler.lua:33: in main chunk                                          \r\n        [C]: in function 'dofile'                                                       \r\n        /usr/local/lib/luarocks/rocks/trepl/scm-1/bin/th:129: in main chunk             \r\n        [C]: at 0x0000cf89                                                              \r\n```\r\nRunning the same code on a Intel machine with Ubuntu 14.04 and a GeForce GTX 780 this doesn't happen. A similar error, though, happened on another Intel machine with Ubuntu 14.04 and a Tesla K40c while trying to run OverFeat.\r\n\r\nMoreover, this error does not happen if I load the model and process the `SpatialMaxPooling` layer only. Instead, if I run all the previous layers, one by one, then it fails at the `SpatialMaxPooling` one with the \"too many resources requested for launch\" Cuda error message.\r\n\r\nI believe it has to do something with the registers available per block. Perhaps the TK1 has more limited resources and the `SpatialMaxsampling` is trying to allocate too many registers."},"comment":{"url":"https://api.github.com/repos/torch/cunn/issues/comments/88195758","html_url":"https://github.com/torch/cunn/issues/32#issuecomment-88195758","issue_url":"https://api.github.com/repos/torch/cunn/issues/32","id":88195758,"user":{"login":"soumith","id":1310570,"avatar_url":"https://avatars.githubusercontent.com/u/1310570?v=3","gravatar_id":"","url":"https://api.github.com/users/soumith","html_url":"https://github.com/soumith","followers_url":"https://api.github.com/users/soumith/followers","following_url":"https://api.github.com/users/soumith/following{/other_user}","gists_url":"https://api.github.com/users/soumith/gists{/gist_id}","starred_url":"https://api.github.com/users/soumith/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/soumith/subscriptions","organizations_url":"https://api.github.com/users/soumith/orgs","repos_url":"https://api.github.com/users/soumith/repos","events_url":"https://api.github.com/users/soumith/events{/privacy}","received_events_url":"https://api.github.com/users/soumith/received_events","type":"User","site_admin":false},"created_at":"2015-03-31T18:17:03Z","updated_at":"2015-03-31T18:17:03Z","body":"on the Tegra, this likely is a block limitation. CuDNN is much more well-written for this."}}