Hi, the interface to ViennaCL [1] has just been merged to 'next', enabling PETSc to use OpenCL-enabled devices (most notably Intel's Xeon Phi and GPUs from AMD in addition to the existing NVIDIA bindings). I tested it with Vector-, Matrix-, and KSP- examples.
The new bindings are enabled by the configure flags --download-viennacl --with-opencl-include=/path/to/OpenCL-Headers --with-opencl-lib=/path/to/libOpenCL.so The OpenCL headers can be obtained on the Khronos webpage [2] and are often available via package managers, e.g. $> sudo apt-get install opencl-headers or $> sudo yam install opencl-headers In such case, the OpenCL include directory is typically /usr/include (BuildSystem may not detect these headers correctly on Mac OS, I'm working on this). The OpenCL library comes with your graphics driver and is usually located at /usr/lib/. There is no separate compiler as for CUDA needed! FAQ: - What is the performance difference between OpenCL and CUDA for GPUs? My experience is that for large problem sizes they are equivalent for almost all linear algebra kernels. For small problem sizes (kernel execution less than 1ms), CUDA is currently superior because of lower latency. - Which solvers can I use with the ViennaCL-bindings? The same as with CUSP. Most notably the usual CG, BiCGS, GMRES. - Which preconditioners are provided in the ViennaCL-bindings? Currently none. You can, however, use all the standard CPU-based preconditioners in PETSc together with ViennaCL matrices and vectors. - Which command line options do I need to use? Use -vec_type viennacl -mat_type aijviennacl On Intel's Xeon Phi you also need to pass -viennacl_device_accelerator. (If you read this email in an archive: Check the manual for current flags). Best regards, Karli [1] http://viennacl.sourceforge.net/ [2] http://www.khronos.org/registry/cl/
