math/libxsmm 1.17_1 DragonFly

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.