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Port details on branch 2022Q3
onednn Intel(R) Math Kernel Library for Deep Neural Networks
2.6 math on this many watch lists=0 search for ports that depend on this port Find issues related to this port Report an issue related to this port View this port on Repology. pkg-fallout 2.6Version of this port present on the latest quarterly branch.
Maintainer: yuri@FreeBSD.org search for ports maintained by this maintainer
Port Added: 2022-08-14 00:33:30
Last Update: 2022-07-23 18:03:21
Commit Hash: 91e7168
License: APACHE20
WWW:
https://01.org/onednn
Description:
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 framework on Intel(R) architecture. Intel(R) MKL-DNN contains vectorized and threaded building blocks which you can use to implement deep neural networks (DNN) with C and C++ interfaces. DNN functionality optimized for Intel architecture is also included in Intel(R) Math Kernel Library (Intel(R) MKL). API in this implementation is not compatible with Intel MKL-DNN and does not include certain new and experimental features. WWW: https://01.org/onednn
Homepage    cgit ¦ Codeberg ¦ GitHub ¦ GitLab ¦ SVNWeb - no subversion history for this port

Manual pages:
FreshPorts has no man page information for this port.
pkg-plist: as obtained via: make generate-plist
Expand this list (43 items)
Collapse this list.
  1. @ldconfig
  2. /usr/local/share/licenses/onednn-2.6/catalog.mk
  3. /usr/local/share/licenses/onednn-2.6/LICENSE
  4. /usr/local/share/licenses/onednn-2.6/APACHE20
  5. include/dnnl.h
  6. include/dnnl.hpp
  7. include/dnnl_config.h
  8. include/dnnl_debug.h
  9. include/dnnl_ocl.h
  10. include/dnnl_ocl.hpp
  11. include/dnnl_sycl.h
  12. include/dnnl_sycl.hpp
  13. include/dnnl_sycl_types.h
  14. include/dnnl_threadpool.h
  15. include/dnnl_threadpool.hpp
  16. include/dnnl_threadpool_iface.hpp
  17. include/dnnl_types.h
  18. include/dnnl_version.h
  19. include/oneapi/dnnl/dnnl.h
  20. include/oneapi/dnnl/dnnl.hpp
  21. include/oneapi/dnnl/dnnl_config.h
  22. include/oneapi/dnnl/dnnl_debug.h
  23. include/oneapi/dnnl/dnnl_ocl.h
  24. include/oneapi/dnnl/dnnl_ocl.hpp
  25. include/oneapi/dnnl/dnnl_ocl_types.h
  26. include/oneapi/dnnl/dnnl_sycl.h
  27. include/oneapi/dnnl/dnnl_sycl.hpp
  28. include/oneapi/dnnl/dnnl_sycl_types.h
  29. include/oneapi/dnnl/dnnl_threadpool.h
  30. include/oneapi/dnnl/dnnl_threadpool.hpp
  31. include/oneapi/dnnl/dnnl_threadpool_iface.hpp
  32. include/oneapi/dnnl/dnnl_types.h
  33. include/oneapi/dnnl/dnnl_version.h
  34. lib/cmake/dnnl/dnnl-config-version.cmake
  35. lib/cmake/dnnl/dnnl-config.cmake
  36. lib/cmake/dnnl/dnnl-targets-release.cmake
  37. lib/cmake/dnnl/dnnl-targets.cmake
  38. lib/libdnnl.so
  39. lib/libdnnl.so.2
  40. lib/libdnnl.so.2.6
  41. @owner
  42. @group
  43. @mode
Collapse this list.
Dependency lines:
  • onednn>0:math/onednn
To install the port:
cd /usr/ports/math/onednn/ && make install clean
To add the package, run one of these commands:
  • pkg install math/onednn
  • pkg install onednn
NOTE: If this package has multiple flavors (see below), then use one of them instead of the name specified above.
PKGNAME: onednn
Flavors: there is no flavor information for this port.
NOT_FOR_ARCHS: armv6 armv7 i386 mips powerpc powerpcspe
distinfo:
TIMESTAMP = 1651423771 SHA256 (oneapi-src-oneDNN-v2.6_GH0.tar.gz) = 9695640f55acd833ddcef4776af15e03446c4655f9296e5074b1b178dd7a4fb2 SIZE (oneapi-src-oneDNN-v2.6_GH0.tar.gz) = 5840464

No package information for this port in our database
Sometimes this happens. Not all ports have packages.
Dependencies
NOTE: FreshPorts displays only information on required and default dependencies. Optional dependencies are not covered.
Build dependencies:
  1. cmake : devel/cmake
  2. ninja : devel/ninja
There are no ports dependent upon this port

Configuration Options:
===> The following configuration options are available for onednn-2.6: ====> Use CPU-specific optimizations: you have to select exactly one of them SIMD_DEFAULT=on: Default, no non-default SIMD instructions are used SIMD_NATIVE=off: Optimize for this CPU SIMD_SSE41=off: Use SSE4.1 instructions ====> Threading runtime for CPU engines: you have to select exactly one of them OPENMP=on: Parallel processing support via OpenMP TBB=off: Threading Building Blocks SEQ=off: Sequential (no parallelism) THREADPOOL_STANDALONE=off: Threadpool based on the standalone implementation THREADPOOL_EIGEN=off: Threadpool based on the Eigen implementation THREADPOOL_TBB=off: Threadpool based on the TBB implementation ===> Use 'make config' to modify these settings
Options name:
math_onednn
USES:
cmake compiler:c++11-lang localbase:ldflags
FreshPorts was unable to extract/find any pkg message
Master Sites:
Expand this list (1 items)
Collapse this list.
  1. https://codeload.github.com/oneapi-src/oneDNN/tar.gz/v2.6?dummy=/
Collapse this list.

Number of commits found: 1

Commit History - (may be incomplete: for full details, see links to repositories near top of page)
CommitCreditsLog message
2.6
23 Jul 2022 18:03:21
commit hash: 91e71683e216c1f961be2658d2f970ae5be6c829commit hash: 91e71683e216c1f961be2658d2f970ae5be6c829commit hash: 91e71683e216c1f961be2658d2f970ae5be6c829commit hash: 91e71683e216c1f961be2658d2f970ae5be6c829 files touched by this commit
Yuri Victorovich (yuri) search for other commits by this committer
math/onednn: Broken on systems where OpenMP isn't enabled

Reported by:	fallout

(cherry picked from commit 0c581d00b14e65df205e0f45de259414ae3d63c6)

Number of commits found: 1