[CUDA cc] 顯示卡計算能力分析 (以GT710為例)(未成功安裝)
發表於 : 2022-07-11, 11:57
參考資料:
Nvidia CUDA cc(計算能力) Table:https://developer.nvidia.com/cuda-gpus#compute
https://forums.developer.nvidia.com/t/h ... 1-0/147053
https://forums.developer.nvidia.com/t/w ... 0/146956/4
1.透過評測網站確認CUDA版本
https://www.techpowerup.com/gpu-specs/g ... -710.c1990
2.維基百科
https://zh.wikipedia.org/zh-tw/CUDA#%E6 ... 5%E5%86%B5
3.NVIDIA GPU Computing Toolkit
4.最低驅動程式版本支援
https://docs.nvidia.com/cuda/cuda-toolk ... r-versions
5.各代顯示卡版本最終支援版本
https://docs.nvidia.com/deploy/cuda-com ... x.html#faq
6.總結:目前(2022/07/11)GT710 最後支援及硬體資訊
pytorch11.3 相容於 CUDA 11.4
https://github.com/pytorch/pytorch/issues/75992
CUDA:
10.2
11.4 Update 4(失敗:可能是需要獨立安裝binary-待測試)
下載點:11.4-4失敗
(根據CUDA Toolkit and Corresponding Driver Versions)
CC:3.5
DRIVER:cuda11.4 >=472.50 / cuda 10.2 >=441.22
PYTORCH:目前最新版(1.12.0/cuda 10.2 僅可使用於1.8.2 LTS)
https://pytorch.org/get-started/locally/
PYTHON:目前最新版
Nvidia CUDA cc(計算能力) Table:https://developer.nvidia.com/cuda-gpus#compute
https://forums.developer.nvidia.com/t/h ... 1-0/147053
https://forums.developer.nvidia.com/t/w ... 0/146956/4
1.透過評測網站確認CUDA版本
https://www.techpowerup.com/gpu-specs/g ... -710.c1990
2.維基百科
https://zh.wikipedia.org/zh-tw/CUDA#%E6 ... 5%E5%86%B5
3.NVIDIA GPU Computing Toolkit
代碼: 選擇全部
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.0\extras\demo_suite>deviceQuery.exe
deviceQuery.exe Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "GeForce GT 710"
CUDA Driver Version / Runtime Version 11.0 / 11.0
CUDA Capability Major/Minor version number: 3.5
Total amount of global memory: 2048 MBytes (2147483648 bytes)
( 1) Multiprocessors, (192) CUDA Cores/MP: 192 CUDA Cores
GPU Max Clock rate: 954 MHz (0.95 GHz)
Memory Clock rate: 2505 Mhz
Memory Bus Width: 64-bit
L2 Cache Size: 524288 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: zu bytes
Total amount of shared memory per block: zu 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: zu bytes
Texture alignment: zu bytes
Concurrent copy and kernel execution: Yes with 1 copy engine(s)
Run time limit on kernels: Yes
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Disabled
CUDA Device Driver Mode (TCC or WDDM): WDDM (Windows Display Driver Model)
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 / 1 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 11.0, CUDA Runtime Version = 11.0, NumDevs = 1, Device0 = GeForce GT 710
Result = PASShttps://docs.nvidia.com/cuda/cuda-toolk ... r-versions
5.各代顯示卡版本最終支援版本
https://docs.nvidia.com/deploy/cuda-com ... x.html#faq
6.總結:目前(2022/07/11)GT710 最後支援及硬體資訊
pytorch11.3 相容於 CUDA 11.4
https://github.com/pytorch/pytorch/issues/75992
CUDA:
10.2
11.4 Update 4(失敗:可能是需要獨立安裝binary-待測試)
下載點:11.4-4失敗
(根據CUDA Toolkit and Corresponding Driver Versions)
CC:3.5
DRIVER:cuda11.4 >=472.50 / cuda 10.2 >=441.22
PYTORCH:目前最新版(1.12.0/cuda 10.2 僅可使用於1.8.2 LTS)
https://pytorch.org/get-started/locally/
PYTHON:目前最新版