2.3 KiB
2.3 KiB
Mailing list
We have a GitHub discussions forum to discuss usage and development of OpenBLAS. We also have a Google group for users and a Google group for development of OpenBLAS.
Donations
You can read OpenBLAS statement of receipts and disbursement and cash balance on google doc. A backer list is available on GitHub.
We welcome the hardware donation, including the latest CPU and boards.
Acknowledgements
This work is partially supported by
- Research and Development of Compiler System and Toolchain for Domestic CPU, National S&T Major Projects: Core Electronic Devices, High-end General Chips and Fundamental Software (No.2009ZX01036-001-002)
- National High-tech R&D Program of China (Grant No.2012AA010903)
Users of OpenBLAS
- Julia - a high-level, high-performance dynamic programming language for technical computing
- Ceemple v1.0.3 (C++ technical computing environment), including OpenBLAS, Qt, Boost, OpenCV and others. The only solution with immediate-recompilation of C++ code. Available from Ceemple C++ Technical Computing.
- netlib-java and various upstream libraries, allowing OpenBLAS to be used from languages on the Java Virtual Machine.
Publications
2013
- Wang Qian, Zhang Xianyi, Zhang Yunquan, Qing Yi, AUGEM: Automatically Generate High Performance Dense Linear Algebra Kernels on x86 CPUs, In the International Conference for High Performance Computing, Networking, Storage and Analysis (SC'13), Denver CO, November 2013. [pdf]
2012
- Zhang Xianyi, Wang Qian, Zhang Yunquan, Model-driven Level 3 BLAS Performance Optimization on Loongson 3A Processor, 2012 IEEE 18th International Conference on Parallel and Distributed Systems (ICPADS), 17-19 Dec. 2012.