gpu-burn | Microway 's improved version of GPU Burn | GPU library

by Microway C++ Version: v0.4.5 License: GPL-3.0

X-Ray Key Features Code Snippets(2)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | gpu-burn Summary

gpu-burn is a C++ library typically used in Hardware, GPU, Pytorch applications. gpu-burn has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

Microway's improved version of GPU Burn

Support

Quality

Security

License

Reuse

Support

gpu-burn has a low active ecosystem.

It has 66 star(s) with 22 fork(s). There are 4 watchers for this library.

It had no major release in the last 12 months.

There are 4 open issues and 1 have been closed. On average issues are closed in 1 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of gpu-burn is v0.4.5

Quality

gpu-burn has 0 bugs and 0 code smells.

Security

gpu-burn has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

gpu-burn code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

gpu-burn is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

gpu-burn releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

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gpu-burn Key Features

No Key Features are available at this moment for gpu-burn.

gpu-burn Examples and Code Snippets

Installation

C++

Lines of Code : 7

License : Strong Copyleft (GPL-3.0)

Copy

VERSION=0.4.6
fpm -t rpm -s dir --prefix=/usr                                             \
    --name gpu-burn -v ${VERSION}                                           \
    --vendor Microway --license GPLv3                                       \

Execution

C++

Lines of Code : 2

License : Strong Copyleft (GPL-3.0)

Copy

gpu_burn $(( 60 * 60 ))

gpu_burn -d $(( 60 * 60 ))

Community Discussions

Trending Discussions on gpu-burn

CUDA mathfunctions.hpp compiler error on Mac OS: cannot overload functions distinguished by return type

QUESTION

CUDA mathfunctions.hpp compiler error on Mac OS: cannot overload functions distinguished by return type

Asked 2019-Apr-17 at 15:18

I tried to compile the code from https://github.com/wilicc/gpu-burn using the following Makefile. It is a GPU burner using CUDA and my Mac indeed has the GT750M.

...

ANSWER

Answered 2019-Apr-17 at 15:18

A workaround to this is to simply edit math_functions.hpp (and also math_functions.h in my case) and comment out the offending lines.

Source https://stackoverflow.com/questions/55461090

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

Vulnerabilities

No vulnerabilities reported

Install gpu-burn

An RPM can be created by running the following from the base directory:. A DEB can be created by replacing the -t rpm above with -t deb.

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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