Hello, I ran into the problem, my graphics card is Tesla K80 , and the official website shows that its Compute Capability is 3.7. However, I tried to use deviceQuery and found that the compute capability is 3.5 . This causes me to be unable to use pytorch version 1.3 or higher (compiling from source code may solve). What is the cause of this?
Here is the log:
Device 0: "Tesla K80" CUDA Driver Version / Runtime Version 9.2 / 9.2 CUDA Capability Major/Minor version number: 3.5 Total amount of global memory: 11441 MBytes (11996954624 bytes) (13) Multiprocessors, (192) CUDA Cores/MP: 2496 CUDA Cores GPU Max Clock rate: 562 MHz (0.56 GHz) Memory Clock rate: 2505 Mhz Memory Bus Width: 384-bit L2 Cache Size: 1572864 bytes Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096) Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 2048 layers Total amount of constant memory: 65536 bytes Total amount of shared memory per block: 49152 bytes Total number of registers available per block: 65536 Warp size: 32 Maximum number of threads per multiprocessor: 2048 Maximum number of threads per block: 1024 Max dimension size of a thread block (x,y,z): (1024, 1024, 64) Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535) Maximum memory pitch: 2147483647 bytes Texture alignment: 512 bytes Concurrent copy and kernel execution: Yes with 2 copy engine(s) Run time limit on kernels: No Integrated GPU sharing Host Memory: No Support host page-locked memory mapping: Yes Alignment requirement for Surfaces: Yes Device has ECC support: Enabled Device supports Unified Addressing (UVA): Yes Device supports Compute Preemption: No Supports Cooperative Kernel Launch: No Supports MultiDevice Co-op Kernel Launch: No Device PCI Domain ID / Bus ID / location ID: 0 / 6 / 0