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15.0 > Libraries > libxsmm (1.17)

  LIBXSMM is a library for specialized dense and sparse matrix 
operations as well as for deep learning primitives such as small
convolutions. The library is targeting Intel Architecture with
Intel SSE, Intel AVX, Intel AVX2, Intel AVX512 (with VNNI and
Bfloat16), and Intel AMX (Advanced Matrix Extensions) supported by
future Intel processor code-named Sapphire Rapids. Code generation
is mainly based on Just-In-Time (JIT) code specialization for
compiler-independent performance (matrix multiplications, matrix
transpose/copy, sparse functionality, and deep learning).
LIBXSMM is suitable for "build once and deploy everywhere",
i.e., no special target flags are needed to exploit the available
performance. Supported GEMM datatypes are: FP64, FP32, bfloat16,
int16, and int8.

NOTE: the library does not support 32-bit architecture (64-bit only)

Maintained by: William PC
Keywords: dense-matrix,sparse-matrix,deep-learning
ChangeLog: libxsmm

Homepage:
https://github.com/libxsmm/libxsmm

Source Downloads (64bit):
libxsmm-1.17.tar.gz (bef3b02f8837b0eed1ea334045da0524)

Download SlackBuild:
libxsmm.tar.gz
libxsmm.tar.gz.asc (FAQ)

(the SlackBuild does not include the source)

Individual Files:
README
libxsmm.SlackBuild
libxsmm.info
slack-desc

Validated for Slackware 15.0

See our HOWTO for instructions on how to use the contents of this repository.

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ftp git cgit http rsync

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