User: eschnett Date: 2012/05/28 02:02 PM
Removed: /about/releases/ opencl.html
Log: Remove notes again
File Changes:
Directory: /about/releases/ ===========================
File [removed]: opencl.html Delta lines: +0 -45 =================================================================== --- about/releases/opencl.html 2012-05-28 18:56:36 UTC (rev 857) +++ about/releases/opencl.html 2012-05-28 19:02:16 UTC (rev 858) @@ -1,45 +0,0 @@ -<h3>Accelerator Support</h3> - -<p>This release of the Einstein Toolkit adds support for GPUs and - other accelerators. This support comprises three levels of - abstraction, ranging from merely building and running both CUDA and - OpenCL code, to automated code generation targetting GPUs instead of - CPUs. As with any other programming paradigm (such as MPI or - OpenMP), the performance benefits depend on the particular - algorithms used and optimisations that are applied. In addition, the - Simulation Factory greatly aids portability to a wide range of - computing systems.</p> - - <!-- This additional text only for the details release notes --> - -<p>At the lowest level, Cactus now supports compiling, building, and - running with either CUDA or OpenCL. CUDA is supported as new - language in addition to C, C++, and Fortran; OpenCL is supported as - an external library, and builds and executes compute kernels via - run-time calls. Details are described in the user's guide (for CUDA) - and in thorn <tt>ExternalLibraries/OpenCL</tt> (for OpenCL).</p> - -<p>Many accelerator platforms today separate between host memory and - device memory, and require explicit copy or map operations to - transfer data. An intermediate level of abstraction aids - transferring grid variables between host and device, using schedule - declarations to keep track of which data are needed where, and - minimising expensive data transfers. For OpenCL, there is a compact - API to build and execute compute kernels at run time. Details are - described in thorns <tt>CactusUtils/Accelerator</tt> - and <tt>CactusUtils/OpenCLRunTime</tt> (with example parameter - file).</p> - -<p>Finally, the code generation - system <a href="http://kranccode.org/"><i>Kranc</i></a> has been - extended to be able to produce either C++ or OpenCL code, based on - the infrastructure described above. This allows writing GPU code in - a very high-level manner. However, it needs to be stated that the - efficiency of the generated code depends on many variables, - including e.g. the finite differencing stencil radius and the number - of operations in the generated compute kernels. Non-trivial kernels - typically require system-dependent tuning to execute efficiently, as - GPUs and other accelerators generally show a rather unforgiving - performance behaviour. The thorns <tt>McLachlan/ML_WaveToy</tt> and - <tt>McLachlan/ML_WaveToy_CL</tt> are examples, generated from the - same Kranc script, showing the generated C++ and OpenCL code.</p>