diff options
author | Cedric Nugteren <web@cedricnugteren.nl> | 2022-04-25 20:15:07 +0200 |
---|---|---|
committer | GitHub <noreply@github.com> | 2022-04-25 20:15:07 +0200 |
commit | df0e492d3996e71cf79c7ac0e504651fd2447ce1 (patch) | |
tree | 0753d4f43b1040bca1092de4c68bfad022a33f98 | |
parent | 9e2ccb7f2b7405f72cf5bdb0a2c2dd20ab519cbd (diff) | |
parent | a7cdf3f0fa166f57f6de0daae807d35a0da08b95 (diff) |
Merge pull request #434 from CNugteren/update_test_status_machines
Remove old test machines and add new ones
-rw-r--r-- | README.md | 20 |
1 files changed, 15 insertions, 5 deletions
@@ -2,11 +2,21 @@ CLBlast: The tuned OpenCL BLAS library ================ -| | Build status | Tests on Intel CPU | Tests on NVIDIA GPU | Other tests | -|-----|-----|-----|-----|-----| -| Windows | [![Build Status](https://ci.appveyor.com/api/projects/status/github/cnugteren/clblast?branch=master&svg=true)](https://ci.appveyor.com/project/CNugteren/clblast) | [![Build Status](http://ci.arrayfire.org:8010/badges/clblast-windows-intel-i7-4790k.svg)](http://ci.arrayfire.org:8010/#/builders/clblast-windows-intel-i7-4790k) | [![Build Status](http://ci.arrayfire.org:8010/badges/clblast-windows-nvidia-k5000.svg)](http://ci.arrayfire.org:8010/#/builders/clblast-windows-nvidia-k5000) | N/A | -| Linux | [![Build Status](https://travis-ci.org/CNugteren/CLBlast.svg?branch=master)](https://travis-ci.org/CNugteren/CLBlast/branches) | [![Build Status](http://ci.arrayfire.org:8010/badges/clblast-linux-intel-e5-2620-v4.svg)](http://ci.arrayfire.org:8010/#/builders/clblast-linux-intel-e5-2620-v4) | [![Build Status](http://ci.arrayfire.org:8010/badges/clblast-linux-nvidia-k80.svg)](http://ci.arrayfire.org:8010/#/builders/clblast-linux-nvidia-k80) | N/A | -| OS X | [![Build Status](https://travis-ci.org/CNugteren/CLBlast.svg?branch=master)](https://travis-ci.org/CNugteren/CLBlast/branches) | [![Build Status](http://ci.arrayfire.org:8010/badges/clblast-osx-intel-i5-4278U.svg)](http://ci.arrayfire.org:8010/#/builders/clblast-osx-intel-i5-4278U) | N/A | N/A | +| Platform | Build status | +|-----|-----| +| Windows | [![Build Status](https://ci.appveyor.com/api/projects/status/github/cnugteren/clblast?branch=master&svg=true)](https://ci.appveyor.com/project/CNugteren/clblast) | +| Linux | [![Build Status](https://travis-ci.org/CNugteren/CLBlast.svg?branch=master)](https://travis-ci.org/CNugteren/CLBlast/branches) | +| OS X | [![Build Status](https://travis-ci.org/CNugteren/CLBlast.svg?branch=master)](https://travis-ci.org/CNugteren/CLBlast/branches) | + +| Test machine (thanks to [ArrayFire](https://ci.arrayfire.org:8010/#/builders)) | Test status | +|-----|-----| +| clblast-linux-nvidia-a100 | [![Test Status](http://ci.arrayfire.org:8010/badges/clblast-linux-nvidia-a100.svg)](http://ci.arrayfire.org:8010/#/builders/clblast-linux-nvidia-a100) | +| clblast-linux-nvidia-k80 | [![Test Status](http://ci.arrayfire.org:8010/badges/clblast-linux-nvidia-k80.svg)](http://ci.arrayfire.org:8010/#/builders/clblast-linux-nvidia-k80) | +| clblast-linux-nvidia-p100 | [![Test Status](http://ci.arrayfire.org:8010/badges/clblast-linux-nvidia-p100.svg)](http://ci.arrayfire.org:8010/#/builders/clblast-linux-nvidia-p100) | +| clblast-linux-nvidia-t4 | [![Test Status](http://ci.arrayfire.org:8010/badges/clblast-linux-nvidia-t4.svg)](http://ci.arrayfire.org:8010/#/builders/clblast-linux-nvidia-t4) | +| clblast-linux-nvidia-v100 | [![Test Status](http://ci.arrayfire.org:8010/badges/clblast-linux-nvidia-v100.svg)](http://ci.arrayfire.org:8010/#/builders/clblast-linux-nvidia-v100) | +| clblast-windows-amd-r9 | [![Test Status](http://ci.arrayfire.org:8010/badges/clblast-windows-amd-r9.svg)](http://ci.arrayfire.org:8010/#/builders/clblast-windows-amd-r9) | +| clblast-windows-nvidia-m6000 | [![Test Status](http://ci.arrayfire.org:8010/badges/clblast-windows-nvidia-m6000.svg)](http://ci.arrayfire.org:8010/#/builders/clblast-windows-nvidia-m6000) | CLBlast is a modern, lightweight, performant and tunable OpenCL BLAS library written in C++11. It is designed to leverage the full performance potential of a wide variety of OpenCL devices from different vendors, including desktop and laptop GPUs, embedded GPUs, and other accelerators. CLBlast implements BLAS routines: basic linear algebra subprograms operating on vectors and matrices. See [the CLBlast website](https://cnugteren.github.io/clblast) for performance reports on various devices as well as the latest CLBlast news. |