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@@ -4,9 +4,9 @@ CLBlast: The tuned OpenCL BLAS library | | Build status | Tests on Intel CPU | Tests on NVIDIA GPU | Tests on Intel GPU | |-----|-----|-----|-----|-----| -| Windows | [](https://ci.appveyor.com/project/CNugteren/clblast) | [](http://67.207.87.39:8010/#/builders/106) | [](http://67.207.87.39:8010/#/builders/105) | [](http://67.207.87.39:8010/#/builders/107) | -| Linux | [](https://travis-ci.org/CNugteren/CLBlast/branches) | [](http://67.207.87.39:8010/#/builders/97) | [](http://67.207.87.39:8010/#/builders/98) | N/A | -| OS X | [](https://travis-ci.org/CNugteren/CLBlast/branches) | [](http://67.207.87.39:8010/#/builders/110) | N/A | N/A | +| Windows | [](https://ci.appveyor.com/project/CNugteren/clblast) | [](http://ci.arrayfire.org:8010/#/builders/clblast-windows-intel-i7-4790k) | [](http://ci.arrayfire.org:8010/#/builders/clblast-windows-nvidia-k5000) | [](http://ci.arrayfire.org:8010/#/builders/clblast-windows-intel-HD4600) | +| Linux | [](https://travis-ci.org/CNugteren/CLBlast/branches) | [](http://ci.arrayfire.org:8010/#/builders/clblast-linux-intel-e5-2620-v4) | [](http://ci.arrayfire.org:8010/#/builders/clblast-linux-nvidia-k80) | N/A | +| OS X | [](https://travis-ci.org/CNugteren/CLBlast/branches) | [](http://ci.arrayfire.org:8010/#/builders/clblast-osx-intel-i5-4278U) | N/A | N/A | 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. @@ -78,6 +78,7 @@ More detailed documentation is available in separate files: * [Tuning for better performance](doc/tuning.md) * [Testing the library for correctness](doc/testing.md) * [Bindings / wrappers for other languages](doc/bindings.md) +* [More details on the GEMM kernel](doc/details_gemm.md) * [Glossary with some terms explained](doc/glossary.md) @@ -133,6 +134,7 @@ Tuning and testing on a variety of OpenCL devices was made possible by: Hardware/software for this project was contributed by: +* [HPC research group at the University of Bristol](http://uob-hpc.github.io/zoo/) for access to their GPU zoo * [ArrayFire](http://arrayfire.org) for settings up and supporting Buildbot correctness tests on multiple platforms * [JetBrains](https://www.jetbrains.com/clion/) for supply a free CLion IDE license for CLBlast developers * [Travis CI](https://travis-ci.org/CNugteren/CLBlast/branches) and [AppVeyor](https://ci.appveyor.com/project/CNugteren/clblast) for free automated build tests for open-source projects @@ -143,8 +145,8 @@ More information Further information on CLBlast is available through the following links: -* A 20-minute presentation of CLBlast was given at the GPU Technology Conference in May 2017. A recording is available on the [GTC on-demand website](http://on-demand.gputechconf.com/gtc/2017/video/s7280-nugteren-clblast.mp4) (poor audio quality however) and a full slide-set is also available [as PDF](http://on-demand.gputechconf.com/gtc/2017/presentation/s7280-cedric-nugteren-clblast.pdf). -* More in-depth information and experimental results are also available in a scientific paper titled [CLBlast: A Tuned OpenCL BLAS Library](https://arxiv.org/abs/1705.05249) (May 2017, updated April 2018). For CLTune, the inspiration for the included auto-tuner, see also the [CLTune: A Generic Auto-Tuner for OpenCL Kernels](https://arxiv.org/abs/1703.06503) paper. +* A 20-minute presentation of CLBlast was given at the GPU Technology Conference in May 2017. A recording is available on the [GTC on-demand website](http://on-demand.gputechconf.com/gtc/2017/video/s7280-nugteren-clblast.mp4) (poor audio quality however) and a full slide-set is also available [as PDF](http://on-demand.gputechconf.com/gtc/2017/presentation/s7280-cedric-nugteren-clblast.pdf). An updated version was also presented at IWOCL in May 2018. The slide set can be found [here as PDF](https://cnugteren.github.io/downloads/CLBlastIWOCL18.pdf). +* More in-depth information and experimental results are also available in a scientific paper titled [CLBlast: A Tuned OpenCL BLAS Library](https://arxiv.org/abs/1705.05249) (v1 May 2017, updated to v2 in April 2018). For CLTune, the inspiration for the included auto-tuner, see also the [CLTune: A Generic Auto-Tuner for OpenCL Kernels](https://arxiv.org/abs/1703.06503) paper. How to cite this work: |