Just to say that, thanks to Matthew Brett, binary wheels for Mac OS X are now available, for Python versions 2.7, 3.3, and 3.4. This means that, if you're on that platform, you won't have to build from source! As usual, just run `pip install pyviennacl`, and please report any issues you encounter to https://github.com/viennacl/pyviennacl-dev/issues !
Thanks, Toby Toby St Clere Smithe <pyvienn...@tsmithe.net> writes: > Hello everybody, > > I am pleased to announce the 1.0.3 release of PyViennaCL! This release > fixes a number of important bugs, and improves performance on nVidia > Kepler GPUs. The ChangeLog is below, and the associated ViennaCL version > is 1.5.2. > > > About PyViennaCL > ================ > > *PyViennaCL* aims to make fast, powerful GPGPU and heterogeneous > scientific computing really transparently easy, especially for users > already using NumPy for representing matrices. > > PyViennaCL does this by harnessing the `ViennaCL > <http://viennacl.sourceforge.net/>`_ linear algebra and numerical computation > library for GPGPU and heterogeneous systems, thereby making available to > Python > programmers ViennaCL’s fast *OpenCL* and *CUDA* algorithms. PyViennaCL does > this in a way that is idiomatic and compatible with the Python community’s > most > popular scientific packages, *NumPy* and *SciPy*. > > PyViennaCL exposes the following functionality: > > * sparse (compressed, co-ordinate, ELL, and hybrid) and dense > (row-major and column-major) matrices, vectors and scalars on your > compute device using OpenCL; > * standard arithmetic operations and mathematical functions; > * fast matrix products for sparse and dense matrices, and inner and > outer products for vectors; > * direct solvers for dense triangular systems; > * iterative solvers for sparse and dense systems, using the BiCGStab, > CG, and GMRES algorithms; > * iterative algorithms for eigenvalue estimation problems. > > PyViennaCL has also been designed for straightforward use in the context > of NumPy and SciPy: PyViennaCL objects can be constructed using NumPy > arrays, and arithmetic operations and comparisons in PyViennaCL are > type-agnostic. > > See the following link for documentation and example code: > http://viennacl.sourceforge.net/pyviennacl/doc/ > > > Get PyViennaCL > ============== > > PyViennaCL is easily installed from PyPI. > > If you are on Windows, there are binaries for Python versions 2.7, 3.2, > 3.3, and 3.4. > > If you are on Mac OS X and want to provide binaries, then please get in > touch! Otherwise, the installation process will build PyViennaCL from > source, which can take a while. > > If you are on Debian or Ubuntu, binaries are available in Debian testing > and unstable, and Ubuntu utopic. Just run:: > > apt-get install python-pyviennacl python3-pyviennacl > > To install PyViennaCL from PyPI, make sure you've got a recent version > of the *pip* package manager, and run:: > > pip install pyviennacl > > > Bugs and support > ================ > > If you find a problem in PyViennaCL, then please report it at > https://github.com/viennacl/pyviennacl-dev/issues > > > ChangeLog > ========= > > 2014-05-15 Toby St Clere Smithe <pyvienn...@tsmithe.net> > > * Release 1.0.3. > > * Update external/viennacl-dev to version 1.5.2. > [91b7589a8fccc92927306e0ae3e061d85ac1ae93] > > This contains two important fixes: one for a build failure on > Windows (PyViennaCL issue #17) relating to the re-enabling of the > Lanczos algorithm in 1.0.2, and one for an issue relating to > missing support for matrix transposition in the ViennaCL scheduler > (PyViennaCL issue #19, ViennaCL issue #73). > > This release is also benefitial for performance on nVidia Kepler > GPUs, increasing the performance of matrix-matrix multiplications > to 600 GFLOPs in single precision on a GeForce GTX 680. > > * Fix bug when using integers in matrix and vector index key > [dbb1911fd788e66475f5717c1692be49d083a506] > > * Fix slicing of dense matrices (issue #18). > [9c745710ebc2a1066c7074b6c5de61b227017cc6] > > * Enable test for matrix transposition > [9e951103b883a3848aa2115df3edce73d347c09b] > > * Add non-square matrix-vector product test > [21dd29cd10ebe02a96ee23c20ee55401bc6c874f] > > 2014-05-06 Toby St Clere Smithe <pyvienn...@tsmithe.net> > > * Release 1.0.2. > > * Re-enable Lanczos algorithm for eigenvalues (issue #11). > [cbfb41fca3fb1f3db42fd7b3ccb8332b701d1e20] > > * Enable eigenvalue computations for compressed and coordinate > matrices. > [8ecee3b200a92ae99b72653a823c1f60e62f75dd] > > * Fix matrix-vector product for non-square matrices (issue #13). > [bf3aa2bf91339df72b6f7561afaf8b12aad57cda] > > * Link against rt on Linux (issue #12). > [d5784b62b353ebbfd78fe1335fd96971b5089f53] > > > > > Best regards, -- Toby St Clere Smithe http://tsmithe.net ------------------------------------------------------------------------------ "Accelerate Dev Cycles with Automated Cross-Browser Testing - For FREE Instantly run your Selenium tests across 300+ browser/OS combos. 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