test_cuda | simple script to test if there is any GPU memory | GPU library

by xrc10 Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | test_cuda Summary

test_cuda is a Python library typically used in Hardware, GPU applications. test_cuda has no bugs, it has no vulnerabilities and it has low support. However test_cuda build file is not available. You can download it from GitHub.

A simple script to test if there is any GPU memory available.

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Quality

Security

License

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Support

test_cuda has a low active ecosystem.

It has 2 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

test_cuda has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of test_cuda is current.

Quality

test_cuda has 0 bugs and 0 code smells.

Security

test_cuda has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

test_cuda code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

test_cuda does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

test_cuda releases are not available. You will need to build from source code and install.

test_cuda has no build file. You will be need to create the build yourself to build the component from source.

It has 100 lines of code, 6 functions and 3 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

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test_cuda Key Features

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test_cuda Examples and Code Snippets

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Community Discussions

Trending Discussions on test_cuda

Pytorch custom CUDA extension build fails for torch 1.6.0 or higher

CublasLt cublasLtMatmulAlgoGetHeuristic returns CUBLAS_STATUS_INVALID_VALUE for rows major matrix

QUESTION

Pytorch custom CUDA extension build fails for torch 1.6.0 or higher

Asked 2021-May-10 at 13:55

I have a custom CUDA extension for pytorch (https://pytorch.org/tutorials/advanced/cpp_extension.html), which used to work fine with pytorch1.4, CUDA10.1, and Titan Xp GPUs. However, recently we changed our system to new A40 GPUs and CUDA11.1. When I try to build my custom pytorch extension using CUDA11.1, pytorch 1.8.1, gcc 9.3.0, and Ubuntu 20.04 I get the following errors:

...

ANSWER

Answered 2021-May-10 at 13:55

I found the issue. The Intel MKL module wasn't loaded properly and caused the error. After fixing this the compilation worked just fine also with CUDA 11.1 and pytorch 1.8.1!

Source https://stackoverflow.com/questions/67386709

QUESTION

CublasLt cublasLtMatmulAlgoGetHeuristic returns CUBLAS_STATUS_INVALID_VALUE for rows major matrix

Asked 2020-Mar-16 at 12:01

I've just finished to refactor my program to use cublasLt lib for GEMM and I fell into a CUBLAS_STATUS_INVALID_VALUE when executing cublasLtMatmulAlgoGetHeuristic in the function below.

CudaMatrix.cu:product

...

ANSWER

Answered 2020-Mar-16 at 12:01

I did 2 mistakes

The matrixLayout was not properly set, I wrote a function to write it before each multiplication based on the op applied to the matrix.

Additionally I put the matrix memory row major instead of column major.

Now the code is working well for square and non square product and row major memory.

cublaslt_mat_mul.cu

Source https://stackoverflow.com/questions/60671222

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install test_cuda

You can download it from GitHub.
You can use test_cuda like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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