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| Name: onednn-devel | Distribution: openSUSE Tumbleweed |
| Version: 3.14 | Vendor: openSUSE |
| Release: 1.1 | Build date: Sat Oct 24 06:48:44 2026 |
| Group: Unspecified | Build host: reproducible |
| Size: 1336635 | Source RPM: onednn-3.14-1.1.src.rpm |
| Packager: https://bugs.opensuse.org | |
| Url: https://github.com/uxlfoundation/oneDNN | |
| Summary: Header files of Intel Math Kernel Library | |
Intel Math Kernel Library for Deep Neural Networks (Intel 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. This package includes the required headers and library files to develop software with the Intel MKL-DNN.
Apache-2.0
* Sat Oct 24 2026 Martin Pluskal <mpluskal@suse.com>
- Update to 3.14:
* Layer normalization gains RMSNorm mode; sparse memory objects
and sparse matmul are now production status
* Graph API: RMSNorm and Dropout operations, SDPA/GQA fusion
improvements, host-side scalars, experimental grouped (MoE)
matmul
* New quantization support: fp8 primitives, MX dynamic
quantization, NVFP4 scheme and fp4 compressed weights
* x86: initial AVX10.2/AMX support (opt-in), relaxed fp32
accumulation mode, ZenDNN path for AMD Zen (opt-in)
* AArch64: faster SVE/ASIMD matmul, eltwise and softmax; re-enable
the Arm Compute Library backend (the 25.03.1 API break is fixed
on both sides and 3.14 needs ACL >= 53.1, matched here)
and the OpenCL GPU backend (kept off on ppc64le where the
bundled CL headers still break the build via <altivec.h>,
and on unvalidated riscv64);
drop the unpackaged bundled-KleidiAI install droppings
* AArch64 %check: skip test_internals_env_vars_* (new verbose-mode
coverage fails only there) and test_benchdnn_modeC_graph_ci_cpu
(known upstream MHA/dropout reference failures)
* Removed the experimental Graph Compiler backend; BLAS-like
sgemm API and f4_e3m0 type deprecated; legacy SSE4.1/AVX and
old-GPU kernels dropped in favor of generic fallbacks
* No soname change (libdnnl.so.3)
* Pass empty DNNL_ARCH_OPT_FLAGS for portable binaries (upstream
renamed the option and dropped the MKLDNN_ compat shim)
* Enable ONEDNN_BUILD_DOC (upstream flipped its default to OFF)
* Add doxygen-mainpage-path.patch: point USE_MDFILE_AS_MAINPAGE
at the source tree, fixing the doc build (the relative
mainpage.md no longer resolves in out-of-source builds, fatal
since upstream turned doxygen warnings into errors)
* Add doxygen-no-warn-as-error.patch: tolerate doxygen warnings
instead of failing the doc build on them (the doc tree predates
the newer doxygen, which reports hundreds of alias/ref warnings)
* Add ocl-sparse-test-skip-without-gpu.patch: skip the new sparse
memory OpenCL tests when no GPU is present (they failed instead
of skipping like every sibling test)
* CVE-2022-26076 (boo#1208411) was fixed upstream in 2022.1,
before the previously packaged 3.7.3, and this Linux build
loads system libraries only: not affected
* Mon Jul 20 2026 Andreas Schwab <schwab@suse.de>
- Enable build for riscv64
* Tue May 06 2025 Eyad Issa <eyadlorenzo@gmail.com>
- Update to v3.7.3:
* https://github.com/uxlfoundation/oneDNN/releases/tag/v3.7.3
* Various correctness and performance fixes
* Tue Apr 15 2025 Guillaume GARDET <guillaume.gardet@opensuse.org>
- Update to 3.7.2:
* https://github.com/oneapi-src/oneDNN/releases/tag/v3.7.2
- Disable benchdnn_modeC_matmul_ci_cpu test as it reaches timeout
quite often
* Fri Jan 03 2025 Eyad Issa <eyadlorenzo@gmail.com>
- Update to 3.6.2:
* https://github.com/oneapi-src/oneDNN/releases/tag/v3.6.2
* Thu Oct 17 2024 Guillaume GARDET <guillaume.gardet@opensuse.org>
- Update to 3.6:
* https://github.com/oneapi-src/oneDNN/releases/tag/v3.6
* Wed Oct 02 2024 Guillaume GARDET <guillaume.gardet@opensuse.org>
- Add openCL deps for devel package
* Tue Sep 24 2024 Guillaume GARDET <guillaume.gardet@opensuse.org>
- Enable graph component
* Mon Sep 23 2024 Guillaume GARDET <guillaume.gardet@opensuse.org>
- Update to 3.5.3:
* https://github.com/oneapi-src/oneDNN/releases/tag/v3.5.3
* Fri Apr 19 2024 Alessandro de Oliveira Faria <cabelo@opensuse.org>
- Update to 3.4.1:
* Fixed an issue with caching and serialization of primitives in
deterministic mode (7ed604a)
* Introduced memory descriptor serialization API
(4cad420, 929a27a, 9b848c8)
* Fixed incorrect results in fp64 convolution and deconvolution
on Intel GPUs based on Xe-LPG architecture (ebe77b5, 0b399ac,
d748d64, 9f4f3d5, 21a8cae)
* Fixed incorrect results in reorder with large sizes on
Intel CPUs and GPUs (69a111e, 4b72361, 74a343b)
* Reduced creation time for deconvolution primitive on
Intel CPUs (bec487e, 1eab005)
* Fixed performance regression in deconvolution on
Intel CPUs (fbe5b97, 1dd3c6a)
* Removed dangling symblols from static builds
(e92c404, 6f5621a)
* Fixed crash during platform detection on some
AArch64-based systems (406a079)
* Fixed performance regression in int8 deconvolution on
Intel CPUs (7e50e15)
* Fixed handling of zero points for matmul in verbose
logs converter (15c7916)
* Fri Dec 01 2023 Alessandro de Oliveira Faria <cabelo@opensuse.org>
- Update to 3.3.3:
- This is a patch release containing the following changes to v3.3.2:
* Fixed performance regression in int8 convolutions on processors with Intel AVX-512 and Intel DL Boost support (a00661f)
* Fixed race condition during library initialization on Intel Data Center GPU Max Series (7dfcd11)
* Fixed accuracy issue in experimental Graph Compiler with LLVM code generator (8892e7e)
* Disabled int8 RNN implementation for cases with non-trivial strides (2195e4b)
* Fixed incorrect results in bfloat16 convolution implementation on processors with Intel AMX support (9f00af9)
* Fixed incorrect results in fp16 and int8 convolution on Intel Core Ultra integrated GPUs (69cef84, 79bc6cc, c9c0b09)
* Fri Dec 01 2023 Alessandro de Oliveira Faria <cabelo@opensuse.org>
- Update to 3.3.1:
- This is a patch release containing the following changes to v3.3:
* Fixed int8 convolution accuracy issue on Intel GPUs (09c87c7)
* Switched internal stream to in-order mode for NVIDIA and AMD GPUs to avoid synchronization issues (db01d62)
* Fixed runtime error for avgpool_bwd operation in Graph API (d025ef6, 9e0602a, e0dc1b3)
* Fixed benchdnn error reporting for some Graph API cases (98dc9db)
* Fixed accuracy issue in experimental Graph Compiler for int8 MHA variant from StarCoder model (5476ef7)
* Fixed incorrect results for layer normalization with trivial dimensions on Intel GPUs (a2ec0a0)
* Removed redundant synchronization for out-of-order SYCL queues (a96e9b1)
* Fixed runtime error in experimental Graph Compiler for int8 MLP subgraph from LLAMA model (595543d)
* Fixed SEGFAULT in experimental Graph Compiler for fp32 MLP subgraph (4207105)
* Fixed incorrect results in experimental Graph Compiler for MLP subgraph (57e14b5)
* Fixed the issue with f16 inner product primitive with s8 output returning unimplemented on Intel GPUs (bf12207, 800b5e9, ec7054a)
* Fixed incorrect results for int8 deconvolution with zero-points on processors with Intel AMX instructions support (55d2cec)
* Tue Oct 10 2023 Paolo Stivanin <info@paolostivanin.com>
- Update to 3.3:
* 3.3: https://github.com/oneapi-src/oneDNN/releases/tag/v3.3
* 3.2: https://github.com/oneapi-src/oneDNN/releases/tag/v3.2
* 3.1: https://github.com/oneapi-src/oneDNN/releases/tag/v3.1
- Drop upstreamed onednn-fix-gcc13.patch
* Tue Mar 21 2023 Guillaume GARDET <guillaume.gardet@opensuse.org>
- Update to 3.0.1:
* Changes: https://github.com/oneapi-src/oneDNN/releases/tag/v3.0.1
- Skipped 3.0:
* Changes: https://github.com/oneapi-src/oneDNN/releases/tag/v3.0
- Add patch to fix build with GCC13:
* onednn-fix-gcc13.patch
- Disable Arm Compute library support until fixed upstream
https://github.com/oneapi-src/oneDNN/issues/1599
- Drop upstream patches:
* 1428.patch
* fa93750.patch
/usr/include/dnnl.h /usr/include/dnnl.hpp /usr/include/dnnl_config.h /usr/include/dnnl_debug.h /usr/include/dnnl_ocl.h /usr/include/dnnl_ocl.hpp /usr/include/dnnl_sycl.h /usr/include/dnnl_sycl.hpp /usr/include/dnnl_sycl_types.h /usr/include/dnnl_threadpool.h /usr/include/dnnl_threadpool.hpp /usr/include/dnnl_threadpool_iface.hpp /usr/include/dnnl_types.h /usr/include/dnnl_version.h /usr/include/mkl-dnn /usr/include/oneapi /usr/include/oneapi/dnnl /usr/include/oneapi/dnnl/dnnl.h /usr/include/oneapi/dnnl/dnnl.hpp /usr/include/oneapi/dnnl/dnnl_common.h /usr/include/oneapi/dnnl/dnnl_common.hpp /usr/include/oneapi/dnnl/dnnl_common_types.h /usr/include/oneapi/dnnl/dnnl_config.h /usr/include/oneapi/dnnl/dnnl_debug.h /usr/include/oneapi/dnnl/dnnl_graph.h /usr/include/oneapi/dnnl/dnnl_graph.hpp /usr/include/oneapi/dnnl/dnnl_graph_ocl.h /usr/include/oneapi/dnnl/dnnl_graph_ocl.hpp /usr/include/oneapi/dnnl/dnnl_graph_sycl.h /usr/include/oneapi/dnnl/dnnl_graph_sycl.hpp /usr/include/oneapi/dnnl/dnnl_graph_types.h /usr/include/oneapi/dnnl/dnnl_ocl.h /usr/include/oneapi/dnnl/dnnl_ocl.hpp /usr/include/oneapi/dnnl/dnnl_ocl_types.h /usr/include/oneapi/dnnl/dnnl_sycl.h /usr/include/oneapi/dnnl/dnnl_sycl.hpp /usr/include/oneapi/dnnl/dnnl_sycl_types.h /usr/include/oneapi/dnnl/dnnl_threadpool.h /usr/include/oneapi/dnnl/dnnl_threadpool.hpp /usr/include/oneapi/dnnl/dnnl_threadpool_iface.hpp /usr/include/oneapi/dnnl/dnnl_types.h /usr/include/oneapi/dnnl/dnnl_ukernel.h /usr/include/oneapi/dnnl/dnnl_ukernel.hpp /usr/include/oneapi/dnnl/dnnl_ukernel_types.h /usr/include/oneapi/dnnl/dnnl_version.h /usr/include/oneapi/dnnl/dnnl_version_hash.h /usr/include/oneapi/dnnl/dnnl_ze.h /usr/include/oneapi/dnnl/dnnl_ze.hpp /usr/lib64/cmake/dnnl /usr/lib64/cmake/dnnl/dnnl-config-version.cmake /usr/lib64/cmake/dnnl/dnnl-config.cmake /usr/lib64/cmake/dnnl/dnnl-targets-relwithdebinfo.cmake /usr/lib64/cmake/dnnl/dnnl-targets.cmake /usr/lib64/libdnnl.so /usr/share/doc/packages/onednn-devel /usr/share/doc/packages/onednn-devel/README.md /usr/share/licenses/onednn-devel /usr/share/licenses/onednn-devel/LICENSE
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