{"action":"created","issue":{"url":"https://api.github.com/repos/NVIDIA/gvdb-voxels/issues/34","repository_url":"https://api.github.com/repos/NVIDIA/gvdb-voxels","labels_url":"https://api.github.com/repos/NVIDIA/gvdb-voxels/issues/34/labels{/name}","comments_url":"https://api.github.com/repos/NVIDIA/gvdb-voxels/issues/34/comments","events_url":"https://api.github.com/repos/NVIDIA/gvdb-voxels/issues/34/events","html_url":"https://github.com/NVIDIA/gvdb-voxels/issues/34","id":369812280,"node_id":"MDU6SXNzdWUzNjk4MTIyODA=","number":34,"title":"Unable to run samples - cudaMalloc fills all the system memory","user":{"login":"AndreFrelicot","id":2123744,"node_id":"MDQ6VXNlcjIxMjM3NDQ=","avatar_url":"https://avatars1.githubusercontent.com/u/2123744?v=4","gravatar_id":"","url":"https://api.github.com/users/AndreFrelicot","html_url":"https://github.com/AndreFrelicot","followers_url":"https://api.github.com/users/AndreFrelicot/followers","following_url":"https://api.github.com/users/AndreFrelicot/following{/other_user}","gists_url":"https://api.github.com/users/AndreFrelicot/gists{/gist_id}","starred_url":"https://api.github.com/users/AndreFrelicot/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/AndreFrelicot/subscriptions","organizations_url":"https://api.github.com/users/AndreFrelicot/orgs","repos_url":"https://api.github.com/users/AndreFrelicot/repos","events_url":"https://api.github.com/users/AndreFrelicot/events{/privacy}","received_events_url":"https://api.github.com/users/AndreFrelicot/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":2,"created_at":"2018-10-13T15:26:06Z","updated_at":"2018-11-22T00:37:40Z","closed_at":"2018-11-22T00:37:40Z","author_association":"NONE","body":"\r\nI'm building on Windows 10 (tried on Linux Ubuntu also, same problem).\r\n\r\nWhen I run a sample it blocks in function allocReduceStorage : \r\ngvdb_1.1\\shared_cudpp\\src\\cudpp\\app\\reduce_app.cu\r\n```\r\n[...]\r\nvoid allocReduceStorage(CUDPPReducePlan *plan)\r\n...\r\n    case CUDPP_FLOAT:\r\n-->        cudaMalloc(&plan->m_blockSums, blocks * sizeof(float));\r\n        break;\r\n```\r\n\r\nSystem : \r\nVersion\t10.0.17134 Build 17134\r\nProcessor\ti7-8750H\r\nGraphics card:\tNVIDIA GeForce GTX 1070 with Max-Q Design\r\nRAM: 32GB\r\nGVDB: 1.1\r\nCUDA: 10\r\n\r\n------------\r\n\r\n`\r\n\r\n\r\n-\t\tplan\t0x000001f057310b30 {m_threadsPerBlock=256 m_maxBlocks=64 m_blockSums=0xcdcdcdcdcdcdcdcd }\tCUDPPReducePlan *\r\n-\t\tCUDPPPlan\t{m_config={algorithm=CUDPP_REDUCE (3) op=CUDPP_MAX (3) datatype=CUDPP_FLOAT (6) ...} m_numElements=1000000 ...}\tCUDPPPlan\r\n+\t\t__vfptr\t0x00007ffb96c87928 {cudpp_1915x64d.dll!void(* CUDPPReducePlan::`vftable'[2])()} {0x00007ffb96417662 {cudpp_1915x64d.dll!CUDPPReducePlan::`vector deleting destructor'(unsigned int)}}\tvoid * *\r\n+\t\tm_config\t{algorithm=CUDPP_REDUCE (3) op=CUDPP_MAX (3) datatype=CUDPP_FLOAT (6) ...}\tCUDPPConfiguration\r\n\t\tm_numElements\t1000000\tunsigned __int64\r\n\t\tm_numRows\t1\tunsigned __int64\r\n\t\tm_rowPitch\t0\tunsigned __int64\r\n+\t\tm_planManager\t0x000001f0571fe540 {m_deviceProps={name=0x000001f0571fe540 \"GeForce GTX 1070 with Max-Q Design\" uuid=...} }\tCUDPPManager *\r\n\t\tm_threadsPerBlock\t256\tunsigned int\r\n\t\tm_maxBlocks\t64\tunsigned int\r\n\t\tm_blockSums\t0xcdcdcdcdcdcdcdcd\tvoid *\r\n\r\n\r\n\r\n-\t\t(*((CUDPPPlan*)plan)).m_planManager->m_deviceProps\t{name=0x000001f0571fe540 \"GeForce GTX 1070 with Max-Q Design\" uuid={bytes=0x000001f0571fe640 \"ÀæÙþ?ÆÐPÀÇ_¢ñ9¬3... } ...}\tcudaDeviceProp\r\n+\t\tname\t0x000001f0571fe540 \"GeForce GTX 1070 with Max-Q Design\"\tchar[256]\r\n+\t\tuuid\t{bytes=0x000001f0571fe640 \"ÀæÙþ?ÆÐPÀÇ_¢ñ9¬3... }\tCUuuid_st\r\n+\t\tluid\t0x000001f0571fe650 \"û\"\tchar[8]\r\n\t\tluidDeviceNodeMask\t1\tunsigned int\r\n\t\ttotalGlobalMem\t8589934592\tunsigned __int64\r\n\t\tsharedMemPerBlock\t49152\tunsigned __int64\r\n\t\tregsPerBlock\t65536\tint\r\n\t\twarpSize\t32\tint\r\n\t\tmemPitch\t2147483647\tunsigned __int64\r\n\t\tmaxThreadsPerBlock\t1024\tint\r\n+\t\tmaxThreadsDim\t0x000001f0571fe684 {1024, 1024, 64}\tint[3]\r\n+\t\tmaxGridSize\t0x000001f0571fe690 {2147483647, 65535, 65535}\tint[3]\r\n\t\tclockRate\t1265500\tint\r\n\t\ttotalConstMem\t65536\tunsigned __int64\r\n\t\tmajor\t6\tint\r\n\t\tminor\t1\tint\r\n\t\ttextureAlignment\t512\tunsigned __int64\r\n\t\ttexturePitchAlignment\t32\tunsigned __int64\r\n\t\tdeviceOverlap\t1\tint\r\n\t\tmultiProcessorCount\t16\tint\r\n\t\tkernelExecTimeoutEnabled\t1\tint\r\n\t\tintegrated\t0\tint\r\n\t\tcanMapHostMemory\t1\tint\r\n\t\tcomputeMode\t0\tint\r\n\t\tmaxTexture1D\t131072\tint\r\n\t\tmaxTexture1DMipmap\t16384\tint\r\n\t\tmaxTexture1DLinear\t134217728\tint\r\n+\t\tmaxTexture2D\t0x000001f0571fe6e4 {131072, 65536}\tint[2]\r\n+\t\tmaxTexture2DMipmap\t0x000001f0571fe6ec {32768, 32768}\tint[2]\r\n+\t\tmaxTexture2DLinear\t0x000001f0571fe6f4 {131072, 65000, 2097120}\tint[3]\r\n+\t\tmaxTexture2DGather\t0x000001f0571fe700 {32768, 32768}\tint[2]\r\n+\t\tmaxTexture3D\t0x000001f0571fe708 {16384, 16384, 16384}\tint[3]\r\n+\t\tmaxTexture3DAlt\t0x000001f0571fe714 {8192, 8192, 32768}\tint[3]\r\n\t\tmaxTextureCubemap\t32768\tint\r\n+\t\tmaxTexture1DLayered\t0x000001f0571fe724 {32768, 2048}\tint[2]\r\n+\t\tmaxTexture2DLayered\t0x000001f0571fe72c {32768, 32768, 2048}\tint[3]\r\n+\t\tmaxTextureCubemapLayered\t0x000001f0571fe738 {32768, 2046}\tint[2]\r\n\t\tmaxSurface1D\t32768\tint\r\n+\t\tmaxSurface2D\t0x000001f0571fe744 {131072, 65536}\tint[2]\r\n+\t\tmaxSurface3D\t0x000001f0571fe74c {16384, 16384, 16384}\tint[3]\r\n+\t\tmaxSurface1DLayered\t0x000001f0571fe758 {32768, 2048}\tint[2]\r\n+\t\tmaxSurface2DLayered\t0x000001f0571fe760 {32768, 32768, 2048}\tint[3]\r\n\t\tmaxSurfaceCubemap\t32768\tint\r\n+\t\tmaxSurfaceCubemapLayered\t0x000001f0571fe770 {32768, 2046}\tint[2]\r\n\t\tsurfaceAlignment\t512\tunsigned __int64\r\n\t\tconcurrentKernels\t1\tint\r\n\t\tECCEnabled\t0\tint\r\n\t\tpciBusID\t1\tint\r\n\t\tpciDeviceID\t0\tint\r\n\t\tpciDomainID\t0\tint\r\n\t\ttccDriver\t0\tint\r\n\t\tasyncEngineCount\t5\tint\r\n\t\tunifiedAddressing\t1\tint\r\n\t\tmemoryClockRate\t4004000\tint\r\n\t\tmemoryBusWidth\t256\tint\r\n\t\tl2CacheSize\t2097152\tint\r\n\t\tmaxThreadsPerMultiProcessor\t2048\tint\r\n\t\tstreamPrioritiesSupported\t1\tint\r\n\t\tglobalL1CacheSupported\t1\tint\r\n\t\tlocalL1CacheSupported\t1\tint\r\n\t\tsharedMemPerMultiprocessor\t98304\tunsigned __int64\r\n\t\tregsPerMultiprocessor\t65536\tint\r\n\t\tmanagedMemory\t1\tint\r\n\t\tisMultiGpuBoard\t0\tint\r\n\t\tmultiGpuBoardGroupID\t0\tint\r\n\t\thostNativeAtomicSupported\t0\tint\r\n\t\tsingleToDoublePrecisionPerfRatio\t32\tint\r\n\t\tpageableMemoryAccess\t0\tint\r\n\t\tconcurrentManagedAccess\t0\tint\r\n\t\tcomputePreemptionSupported\t0\tint\r\n\t\tcanUseHostPointerForRegisteredMem\t0\tint\r\n\t\tcooperativeLaunch\t0\tint\r\n\t\tcooperativeMultiDeviceLaunch\t0\tint\r\n\t\tsharedMemPerBlockOptin\t0\tunsigned __int64\r\n\t\tpageableMemoryAccessUsesHostPageTables\t0\tint\r\n\t\tdirectManagedMemAccessFromHost\t0\tint\r\n\r\n\r\n\r\n`"},"comment":{"url":"https://api.github.com/repos/NVIDIA/gvdb-voxels/issues/comments/440866318","html_url":"https://github.com/NVIDIA/gvdb-voxels/issues/34#issuecomment-440866318","issue_url":"https://api.github.com/repos/NVIDIA/gvdb-voxels/issues/34","id":440866318,"node_id":"MDEyOklzc3VlQ29tbWVudDQ0MDg2NjMxOA==","user":{"login":"AndreFrelicot","id":2123744,"node_id":"MDQ6VXNlcjIxMjM3NDQ=","avatar_url":"https://avatars1.githubusercontent.com/u/2123744?v=4","gravatar_id":"","url":"https://api.github.com/users/AndreFrelicot","html_url":"https://github.com/AndreFrelicot","followers_url":"https://api.github.com/users/AndreFrelicot/followers","following_url":"https://api.github.com/users/AndreFrelicot/following{/other_user}","gists_url":"https://api.github.com/users/AndreFrelicot/gists{/gist_id}","starred_url":"https://api.github.com/users/AndreFrelicot/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/AndreFrelicot/subscriptions","organizations_url":"https://api.github.com/users/AndreFrelicot/orgs","repos_url":"https://api.github.com/users/AndreFrelicot/repos","events_url":"https://api.github.com/users/AndreFrelicot/events{/privacy}","received_events_url":"https://api.github.com/users/AndreFrelicot/received_events","type":"User","site_admin":false},"created_at":"2018-11-22T00:37:40Z","updated_at":"2018-11-22T00:37:40Z","author_association":"NONE","body":"Thank you, I'll test that \r\n\r\nhttp://arnon.dk/matching-sm-architectures-arch-and-gencode-for-various-nvidia-cards/\r\n\r\nhttps://github.com/tpruvot/ccminer/wiki/Compatibility\r\n\r\n"}}
{"actor":{"display_login":"AndreFrelicot"}}