WebCOUGAR EVENTS. See all events. Thursday, April 13. 11:30 am You Did It Luncheon. Where: Kalamazoo Valley Community College, 6767 W O Ave, Kalamazoo, MI 49009, … WebSparse matrix vector multiplication (SpMV) is heavily used in many important application domains. It’s serial implementation is very simple. From the slide, we can see that the serial implementation only needs 6 line codes. There are many work involved in the optimization of spmv on both CPUs and GPUs.

OpenCL-Darknet: implementation and optimization of OpenCL …

This is the code base of my publication in 2012:Bor-Yiing Su, Kurt Keutzer, "clSpMV: A Cross-Platform OpenCL SpMV Framework on GPUs," in International Conference on Supercomputing (ICS 2012), Italy, June 2012. See more The clSpMV framework optimizes the Sparse Matrix Vector multiplication (SpMV) kernel on OpenCL enabled GPU platforms. Given a sparse matrix, the ultimate goal is to find the best representation of any … See more Bor-Yiing Su, Kurt Keutzer, "clSpMV: A Cross-Platform OpenCL SpMV Framework on GPUs," in International Conference on Supercomputing … See more The clSpMV framework uses the Cocktail Format to store a sparse matrix. The Cocktail Format is a combination of different sparse matrix formats. The idea is to represent … See more The package has two major executables: spmv_cocktail: Given a sparse matrix, analyze it, represent the matrix using the Cocktail Format, and … See more WebclSpMV [19], Zhao et al. [21]! %3 % Compiler Technologies TVM [29] % % % TACO [30] ! % % Intelligent Auto-tuner AlphaSparse ! ! ! Table I compares AlphaSparse with mainstream related works from angles of sparsity, irregularity, and creativity. Compared with artificial format designs and traditional SpMV auto-tuners, AlphaSparse shows its ... truck workshop health and safety

clSpMV - Par Lab - University of California, Berkeley

WebJul 23, 2013 · Sparse matrix-vector multiplication (spMVM) is the most time-consuming kernel in many numerical algorithms and has been studied extensively on all modern processor and accelerator architectures. However, the optimal sparse matrix data storage format is highly hardware-specific, which could become an obstacle when using … WebThe results show substantial and consistent performance improvements for double-precision calculations, outperforming the state-of-the-art ensemble framework clSpMV. We could observe speedup peaks up to 1.94 and a 25% (geometric) average improvement, which can be potentially increased to 43% introducing a simple 1x2 blocking strategy. WebOct 27, 2016 · This work addresses the development of high-performance scientific software for sparse linear algebra, which is an important field of research and forms the foundation of many applications of computational science and engineering, with a special focus on sparse eigenvalue solvers on current and future supercomputers. 1 Highly Influenced PDF truck works of maine