Sparse Matrix-Vector multiplication

Fast Gathering-based SpMxV for Linear Feature Extraction

This algorithm can be used to improve sparse matrix-vector and matrix-matrix multiplication in any numerical computation. As we know, there are lots of applications involving semi-sparse matrix computation in High Performance Computing. Additionally, in popular perceptual computing low-level engines, especially speech and facial recognition, semi-sparse matrices are found to be very common. Therefore, this invention can be applied to those mathematical libraries dedicated to these kinds of recognition engines.
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    Intel® Math Kernel Library (Intel® MKL) is a highly optimized, extensively threaded, and thread-safe library of mathematical functions for engineering, scientific, and financial applications that require maximum performance. The Intel MKL 11.1 packages are now ready for download.

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