Hi,
I’m running the same Julia code using CuArrays etc in two machines, one at home and one at work. At home my code works well, this is a 16Gb RAM, Ubuntu 18.04 linux box with a Geoforce 1050Ti, 4Gb RAM. On the computer at wok I have a Xeon with 32Gb RAM, same ubuntu, and a GPU (don’t remember the model) that has 6Gb. But in this case running the exact same code says
CUDA error: too many resources requested for launch (code 701, ERROR_LAUNCH_OUT_OF_RESOURCES)
Stacktrace:
[1] throw_api_error(::CUDAdrv.cudaError_enum) at /home/mazzanti/.julia/packages/CUDAdrv/Uc14X/src/error.jl:105
[2] macro expansion at /home/mazzanti/.julia/packages/CUDAdrv/Uc14X/src/error.jl:112 [inlined]
[3] cuLaunchKernel(::CuFunction, ::UInt32, ::UInt32, ::UInt32, ::UInt32, ::UInt32, ::UInt32, ::Int64, ::CuStream, ::Array{Ptr{Nothing},1}, ::Ptr{Nothing}) at /home/mazzanti/.julia/packages/CUDAapi/XuSHC/src/call.jl:93
[4] (::CUDAdrv.var"#566#567"{Bool,Int64,CuStream,CuFunction})(::Array{Ptr{Nothing},1}) at /home/mazzanti/.julia/packages/CUDAdrv/Uc14X/src/execution.jl:67
[5] macro expansion at /home/mazzanti/.julia/packages/CUDAdrv/Uc14X/src/execution.jl:33 [inlined]
[6] pack_arguments(::CUDAdrv.var"#566#567"{Bool,Int64,CuStream,CuFunction}, ::CuDeviceArray{Float64,2,CUDAnative.AS.Global}, ::CuDeviceArray{Float64,2,CUDAnative.AS.Global}) at /home/mazzanti/.julia/packages/CUDAdrv/Uc14X/src/execution.jl:10
[7] launch(::CuFunction, ::CuDeviceArray{Float64,2,CUDAnative.AS.Global}, ::Vararg{CuDeviceArray{Float64,2,CUDAnative.AS.Global},N} where N; blocks::Int64, threads::Int64, cooperative::Bool, shmem::Int64, stream::CuStream) at /home/mazzanti/.julia/packages/CUDAdrv/Uc14X/src/execution.jl:60
[8] #571 at /home/mazzanti/.julia/packages/CUDAdrv/Uc14X/src/execution.jl:136 [inlined]
[9] macro expansion at /home/mazzanti/.julia/packages/CUDAdrv/Uc14X/src/execution.jl:95 [inlined]
[10] convert_arguments at /home/mazzanti/.julia/packages/CUDAdrv/Uc14X/src/execution.jl:78 [inlined]
[11] #cudacall#570 at /home/mazzanti/.julia/packages/CUDAdrv/Uc14X/src/execution.jl:135 [inlined]
[12] #cudacall#120 at /home/mazzanti/.julia/packages/CUDAnative/e0IdN/src/execution.jl:217 [inlined]
[13] macro expansion at /home/mazzanti/.julia/packages/CUDAnative/e0IdN/src/execution.jl:198 [inlined]
[14] #call#104 at /home/mazzanti/.julia/packages/CUDAnative/e0IdN/src/execution.jl:170 [inlined]
[15] #_#123 at /home/mazzanti/.julia/packages/CUDAnative/e0IdN/src/execution.jl:345 [inlined]
[16] macro expansion at /home/mazzanti/.julia/packages/CUDAnative/e0IdN/src/execution.jl:109 [inlined]
[17] Log_Unnorm_Probs_CUDA(::CuArray{Float64,2,Nothing}, ::CuArray{Float64,2,Nothing}, ::RBM_net{Float64}, ::Binary_01) at /home/mazzanti/Julia_1/Modules/CUDA/RBM_module_CUDA_J1.jl:152
[18] Log_Z_CUDA(::CuArray{Float64,2,Nothing}, ::RBM_net{Float64}) at /home/mazzanti/Julia_1/Modules/CUDA/RBM_module_CUDA_J1.jl:185
[19] Log_Z_CUDA(::RBM_net{Float64}, ::Int64) at /home/mazzanti/Julia_1/Modules/CUDA/RBM_module_CUDA_J1.jl:300
[20] Log_Z_CUDA(::RBM_net{Float64}; Mblock::Int64) at /home/mazzanti/Julia_1/Modules/CUDA/RBM_module_CUDA_J1.jl:219
[21] Log_Z_CUDA(::RBM_net{Float64}) at /home/mazzanti/Julia_1/Modules/CUDA/RBM_module_CUDA_J1.jl:210
[22] top-level scope at ./In[18]:33
is there a way to fix that? to free resources from within the code?
Best regards and thanks,
Ferran.