CULA is a set of GPU-accelerated linear algebra libraries utilizing the NVIDIA CUDA parallel computing architecture to dramatically improve the computation speed of sophisticated mathematics.
Offering exceptional capability in an easy-to-use package
- Supercomputing performance. The CULA libraries are over 10x faster than the competition.
- Simplicity. Our libraries require no GPU programming experience.
- Advanced interfaces. For usage in C, C++, Fortran, MATLAB, and Python.
- Cross platform support. Available for Linux, Windows, and Mac OS X.
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| Provides accelerated implementations of the LAPACK and BLAS libraries for dense linear algebra. Contains routines for systems solvers, singular value decompositions, and eigenproblems. | Provides tools necessary to rapidly solve large sparse systems using iterative methods. Multiple algorithms, preconditioners, and data storage formats are supported. |
CULA was developed by a team of engineers at EM Photonics in partnership with NVIDIA®. CULA leverages the power of NVIDIA’s Tesla™ many-core computing processor with the CUDA™ architecture for accelerated linear algebra.
