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LIBXSMM is a library for specialized dense and sparse matrix operations as well
as for deep learning primitives such as small convolutions targeting Intel
Architecture. Small matrix multiplication kernels (SMMs) are generated for Intel
SSE, Intel AVX, Intel AVX2, IMCI (KNCni) for Intel Xeon Phi coprocessors (KNC),
and Intel AVX-512 as found in the Intel Xeon Phi processor family (KNL, KNM) and
Intel Xeon processors (SKX). Highly optimized code for small convolutions is
targeting Intel AVX2 and Intel AVX-512, whereas other targets can automatically
leverage specialized SMMs to perform convolutions.
The library supports statically generated code at configuration time (SMMs),
uses optimized code paths based on compiler-generated code as well as Intrinsic
functions, but mainly utilizes Just-In-Time (JIT) code specialization for
compiler-independent performance (matrix multiplications, matrix transpose/copy,
sparse functionality, and small convolutions). LIBXSMM is suitable for "build
once and deploy everywhere" i.e., no special target flags are needed to exploit
the available performance.
WWW: https://github.com/hfp/libxsmm
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