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Floating point computing capacity not match with Orin-x's datasheet #27

Open lix19937 opened 3 days ago

lix19937 commented 3 days ago

  1. Please describe the issue: Floating point computing capacity not match with Orin-x's datasheet

  2. Detailed steps on how to reproduce the issue: Run cuda sample cudaTensorCoreGemm

    
Initializing...
GPU Device 0: "Ampere" with compute capability 8.7

M: 4096 (16 x 256) N: 4096 (16 x 256) K: 4096 (16 x 256) Preparing data for GPU... Required shared memory size: 64 Kb Computing... using high performance kernel compute_gemm Time: 14.465408 ms TFLOPS: 9.50


Run cuda sample 'deviceQuery'

./deviceQuery Starting...

CUDA Device Query (Runtime API) version (CUDART static linking)

Detected 1 CUDA Capable device(s)

Device 0: "Graphics Device" CUDA Driver Version / Runtime Version 11.4 / 11.4 CUDA Capability Major/Minor version number: 8.7 Total amount of global memory: 28969 MBytes (30376570880 bytes) (016) Multiprocessors, (128) CUDA Cores/MP: 2048 CUDA Cores GPU Max Clock rate: 1275 MHz (1.27 GHz) Memory Clock rate: 1275 Mhz Memory Bus Width: 128-bit L2 Cache Size: 4194304 bytes Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384) Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers Total amount of constant memory: 65536 bytes Total amount of shared memory per block: 49152 bytes Total shared memory per multiprocessor: 167936 bytes Total number of registers available per block: 65536 Warp size: 32 Maximum number of threads per multiprocessor: 1536 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: Yes Support host page-locked memory mapping: Yes Alignment requirement for Surfaces: Yes Device has ECC support: Disabled Device supports Unified Addressing (UVA): Yes Device supports Managed Memory: Yes Device supports Compute Preemption: Yes Supports Cooperative Kernel Launch: Yes Supports MultiDevice Co-op Kernel Launch: Yes Device PCI Domain ID / Bus ID / location ID: 0 / 0 / 0 Compute Mode: < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >

deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 11.4, CUDA Runtime Version = 11.4, NumDevs = 1

lix19937 commented 3 days ago

The sample may use old version of WMMA so it has low performance. Please use cudaBlasLT or CUDNN with tensorOP for test.