Skip to main content

gputest

Reporting GPU benchmark results and information.

Installation

Just pip install gputest !

Usage

> gputest

example output:

Distributor ID:	Ubuntu
Description:	Ubuntu 22.04.3 LTS
Release:	22.04
Codename:	jammy
┌──────────────────────────┐
│ Experimental Environment │
└──────────────────────────┘
platform: Linux-5.10.16.3-microsoft-standard-WSL2-x86_64-with-glibc2.35
node: DESKTOP-88GMTT4
time: 2023-10-09 12:44:20.726428
python interpreter: /home/kk/miniconda3/bin/python
python version: 3.11.4 (main, Jul  5 2023, 13:45:01) [GCC 11.2.0]
device: gpu
CUDA version: 12.1
driver version: 537.13
cuDNN version: 8902
nccl version: 2.18.1
gpu usable count: 1
gpu total count: 1
    gpu 0: NVIDIA GeForce RTX 4090, [mem]  1380M / 24564M,  6%,  31°C, 🔋 8
gpu direct communication matrix:
	    GPU0	CPU Affinity	NUMA Affinity	GPU NUMA ID
GPU0	 X 				N/A
cpu: [logical] 24, [physical] 12, [usage] 3.6%
virtual memory: [total] 15.5GB, [avail] 14.2GB, [used] 1.0GB 8.7%
disk usage: [total] 251.0GB, [free] 228.9GB, [used] 9.3GB 3.9%
current dir: /home/kk
user: kk
shell: /bin/bash
python packages version:
    torch: 2.1.0+cu121
    transformers: 4.34.0
    triton: 2.1.0
┌─────────────────────────────────┐
│ Matrix Multiplication Benchmark │
└─────────────────────────────────┘
Matrix: A [16384 x 16384], B [16384 x 16384]
Operation: A @ B
Experiment: 50
Tensor:
    - torch.float16 | 0.05057s (median) | 173.9521 TFLOPS | GPU mem allocated 1.5GB, reserved 1.5GB
    - torch.float32 | 0.16625s (median) | 52.9086 TFLOPS | GPU mem allocated 3.0GB, reserved 4.5GB
┌─────────────────────────────┐
│ Resnet18 Inference Profiler │
└─────────────────────────────┘
---------------------------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  
                             Name    Self CPU %      Self CPU   CPU total %     CPU total  CPU time avg       CPU Mem  Self CPU Mem      CUDA Mem  Self CUDA Mem    # of Calls  
---------------------------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  
                  model_inference         0.16%       1.312ms       100.00%     803.729ms     803.729ms           0 b           0 b           0 b    -110.74 Mb             1  
                     aten::conv2d         0.19%       1.565ms        91.57%     735.938ms      36.797ms           0 b           0 b      47.51 Mb     490.00 Kb            20  
                aten::convolution         0.02%     176.000us        91.56%     735.875ms      36.794ms           0 b           0 b      47.51 Mb           0 b            20  
               aten::_convolution         0.02%     143.000us        91.54%     735.699ms      36.785ms           0 b           0 b      47.51 Mb           0 b            20  
          aten::cudnn_convolution        91.52%     735.556ms        91.52%     735.556ms      36.778ms           0 b           0 b      47.51 Mb      47.51 Mb            20  
                       aten::add_         0.06%     467.000us         0.06%     467.000us      16.679us           0 b           0 b           0 b           0 b            28  
                 aten::batch_norm         0.01%      64.000us         7.91%      63.586ms       3.179ms           0 b           0 b      47.41 Mb       3.83 Mb            20  
     aten::_batch_norm_impl_index         0.01%      62.000us         7.91%      63.551ms       3.178ms           0 b           0 b      47.41 Mb           0 b            20  
           aten::cudnn_batch_norm         7.77%      62.451ms         7.90%      63.489ms       3.174ms           0 b           0 b      47.41 Mb       5.50 Kb            20  
                 aten::empty_like         0.01%      56.000us         0.12%     984.000us      49.200us           0 b           0 b      47.37 Mb           0 b            20  
---------------------------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  ------------  
Self CPU time total: 803.729ms

from gputest.nvidia import get_gpus

for gpu in get_gpus():
	print(gpu.__dict__)
	print(gpu.get_max_clock_speeds())
	print(gpu.get_clock_speeds())
	print(gpu.get_memory_details())
from gpuinfo.windows import get_gpus

for gpu in get_gpus():
	print(gpu.__dict__)

Metadata

Release files for gputest 1.1.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for gputest 1.1.3
File Size Uploaded
gputest-1.1.3.tar.gz 152.1 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for gputest 1.1.3
File Interpreter ABI Platform
gputest-1.1.3-py3-none-any.whl Python 3 none any Details

Total release size: 159.3 kB

Release files / gputest-1.1.3.tar.gz

Download URL gputest-1.1.3.tar.gz
Size 152.1 kB
Tags Source
SHA-256 checksum
How to use checksums
58800374a032d9c5023a4a81fc85883fd5650119d60a1a9b428b4cc142ba4e69
BLAKE2b-256 checksum
How to use checksums
3aac242aa2084d4f26a2cef975ab6a7fe9a70f29b4f0daa9022260017ca44521
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.10.13

Release files / gputest-1.1.3-py3-none-any.whl

Download URL gputest-1.1.3-py3-none-any.whl
Size 7.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
b96311eec9448b53f6e38d7fcfcd52c1ef0ce4d6dff4f54dcfe46ea2d24ea065
BLAKE2b-256 checksum
How to use checksums
4c22d050591ae2831adbcf1f6313f38544c429f4980093a54eb94be92c4a35d5
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.10.13

Release history Release notifications | RSS feed

This release

1.1.3 This release

2 release files

1.1.2

2 release files

1.1.1

2 release files

1.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page