libdnnl1-1.6.3-bp153.1.13 RPM for x86_64

From OpenSuSE Leap 15.3 for x86_64

Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN) is an
open-source performance library for deep-learning applications. The library
accelerates deep-learning applications and frameworks on Intel architecture.
Intel MKL-DNN contains vectorized and threaded building blocks that you can use
to implement deep neural networks (DNN) with C and C++ interfaces.

Provides

• libdnnl1
• libdnnl.so.1()(64bit)
• libdnnl1(x86-64)

Requires

• /sbin/ldconfig
• /sbin/ldconfig
• ld-linux-x86-64.so.2()(64bit)
• ld-linux-x86-64.so.2(GLIBC_2.3)(64bit)
• libOpenCL.so.1()(64bit)
• libOpenCL.so.1(OPENCL_1.0)(64bit)
• libOpenCL.so.1(OPENCL_1.1)(64bit)
• libOpenCL.so.1(OPENCL_1.2)(64bit)
• libOpenCL.so.1(OPENCL_2.0)(64bit)
• libc.so.6()(64bit)
• libc.so.6(GLIBC_2.14)(64bit)
• libc.so.6(GLIBC_2.17)(64bit)
• libc.so.6(GLIBC_2.2.5)(64bit)
• libc.so.6(GLIBC_2.3.4)(64bit)
• libc.so.6(GLIBC_2.4)(64bit)
• libdl.so.2()(64bit)
• libdl.so.2(GLIBC_2.2.5)(64bit)
• libgcc_s.so.1()(64bit)
• libgcc_s.so.1(GCC_3.0)(64bit)
• libgcc_s.so.1(GCC_3.4)(64bit)
• libgomp.so.1()(64bit)
• libgomp.so.1(GOMP_1.0)(64bit)
• libgomp.so.1(GOMP_4.0)(64bit)
• libgomp.so.1(OMP_1.0)(64bit)
• libm.so.6()(64bit)
• libm.so.6(GLIBC_2.2.5)(64bit)
• libm.so.6(GLIBC_2.27)(64bit)
• libm.so.6(GLIBC_2.29)(64bit)
• libpthread.so.0()(64bit)
• libpthread.so.0(GLIBC_2.2.5)(64bit)
• libstdc++.so.6()(64bit)
• libstdc++.so.6(CXXABI_1.3)(64bit)
• libstdc++.so.6(CXXABI_1.3.11)(64bit)
• libstdc++.so.6(CXXABI_1.3.3)(64bit)
• libstdc++.so.6(CXXABI_1.3.5)(64bit)
• libstdc++.so.6(GLIBCXX_3.4)(64bit)
• libstdc++.so.6(GLIBCXX_3.4.11)(64bit)
• libstdc++.so.6(GLIBCXX_3.4.14)(64bit)
• libstdc++.so.6(GLIBCXX_3.4.15)(64bit)
• libstdc++.so.6(GLIBCXX_3.4.18)(64bit)
• libstdc++.so.6(GLIBCXX_3.4.21)(64bit)
• libstdc++.so.6(GLIBCXX_3.4.9)(64bit)
• rpmlib(CompressedFileNames) <= 3.0.4-1
• rpmlib(FileDigests) <= 4.6.0-1
• rpmlib(PayloadFilesHavePrefix) <= 4.0-1
• rpmlib(PayloadIsXz) <= 5.2-1

License

Apache-2.0

Changelog

* Mon Oct 05 2020 Guillaume GARDET <guillaume.gardet@opensuse.org>
  - Obsoletes mkl-dnn* <= %{version}
* Fri Oct 02 2020 Guillaume GARDET <guillaume.gardet@opensuse.org>
  - Rename mkl-dnn to onednn to follow upstream
* Wed Sep 23 2020 Guillaume GARDET <guillaume.gardet@opensuse.org>
  - Update to 1.6.3
  - Drop upstream patch:
    * cmake-no-install-ocl-cmake.patch
* Wed Sep 23 2020 Guillaume GARDET <guillaume.gardet@opensuse.org>
  - Build on aarch64 and ppc64le which are now also supported
  - Provide oneDNN and oneDNN-devel as it is the new official name
* Tue May 05 2020 Tomáš Chvátal <tchvatal@suse.com>
  - Update to 1.4:
    * Performance improvements all over the board
  - Rebase patch cmake-no-install-ocl-cmake.patch
* Tue Mar 24 2020 Tomáš Chvátal <tchvatal@suse.com>
  - Add constraints to not crash during testing on OOM
* Thu Feb 27 2020 Tomáš Chvátal <tchvatal@suse.com>
  - Do not disable LTO there is no actual reason for that
  - Export LD_LIBRARY_PATH to fix older releases build
* Wed Feb 26 2020 Tomáš Chvátal <tchvatal@suse.com>
  - There is no actual reason to not use github tag for tarball
    fetching -> remove the service
  - Format with spec-cleaner
  - Use proper %cmake macros everywhere
  - Add configure options for cmake to set it up in a way we really
    want
  - Add patch from Debian to not install OpenCL cmake finder:
    * cmake-no-install-ocl-cmake.patch
* Thu Feb 20 2020 Christian Goll <cgoll@suse.com>
  - enabled tests
* Thu Jan 30 2020 Christian Goll <cgoll@suse.com>
  - packaged separate benchnn packae with its input files
  - updated to v1.1.3 which includes
    * Fixed the mean and variance memory descriptors in layer
    normalization (65f1908)
    * Fixed the layer normalization formula (c176ceb)
* Wed Jan 08 2020 Christian Goll <cgoll@suse.com>
  - updated to v1.1.2
    * Fixed threading over the spatial in bfloat16 batched
      normalization (017b6c9)
    * Fixed read past end-of-buffer error for int8 convolution (7d6f45e)
    * Fixed condition for dispatching optimized channel blocking in
      fp32 backward convolution on Intel Xeon Phi(TM) processor (846eba1)
    * Fixed fp32 backward convolution for shapes with spatial strides
      over the depth dimension (002e3ab)
    * Fixed softmax with zero sizes on GPU (936bff4)
    * Fixed int8 deconvolution with dilation when ih <= dh (3e3bacb)
    * Enabled back fp32 -> u8 reorder for RNN (a2c2507)
    * Fixed segmentation fault in bfloat16 backward convolution from
      kd_padding=0 computation (52d476c)
    * Fixed segmentation fault in bfloat16 forward convolution due
      to push/pop imbalance (4f6e3d5)
    * Fixed library version for OS X build (0d85005)
    * Fixed padding by channels in concat (a265c7d)
    * Added full text of third party licenses and
      copyright notices to LICENSE file (79f204c)
    * Added separate README for binary packages (28f4c96)
    * Fixed computing per-oc mask in RNN (ff3ffab)
    * Added workaround for number of cores calculation in Xbyak (301b088)
* Mon Feb 11 2019 cgoll@suse.com
  - added ARCH_OPT_FLAGS=""
* Tue Feb 05 2019 Christian Goll <cgoll@suse.com>
  - Initial checking of the Intel(R) Math Kernel Library for
    Deep Neural Networks which can be used by:
    * tensorflow
    * Caffee
    * PyTorch
    and other machine learning tools

Files

/usr/lib64/libdnnl.so.1
/usr/lib64/libdnnl.so.1.6
/usr/lib64/libmkldnn.so.1
/usr/lib64/libmkldnn.so.1.6
/usr/share/doc/packages/libdnnl1
/usr/share/doc/packages/libdnnl1/README.md
/usr/share/licenses/libdnnl1
/usr/share/licenses/libdnnl1/LICENSE

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Fabrice Bellet, Tue Apr 9 15:02:03 2024