Script 'mail_helper' called by obssrc Hello community, here is the log from the commit of package onednn for openSUSE:Factory checked in at 2021-06-04 22:43:13 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Comparing /work/SRC/openSUSE:Factory/onednn (Old) and /work/SRC/openSUSE:Factory/.onednn.new.1898 (New) ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Package is "onednn" Fri Jun 4 22:43:13 2021 rev:4 rq:897415 version:2.2.3 Changes: -------- --- /work/SRC/openSUSE:Factory/onednn/onednn.changes 2021-04-14 10:11:32.989551512 +0200 +++ /work/SRC/openSUSE:Factory/.onednn.new.1898/onednn.changes 2021-06-04 22:43:27.375122186 +0200 @@ -1,0 +2,47 @@ +Thu Jun 3 01:38:56 UTC 2021 - Ferdinand Thiessen <r...@fthiessen.de> + +- Update to version 2.2.3 + * Fixed a bug in int8 depthwise convolution ptimitive with groups + and 1d spatial size for processors with AVX-512 and AVX2 support + * Fixed correctness issue for PReLU primitive + * Fixed corretness issue in reorder for blocked layouts with + zero padding + * Improved performance of weights reorders used by BRGEMM-based + convolution primitive for processors with AVX-512 support + * Added -fp-model=precise build flag for DPC++ code + * Fixed potential memory leak in matmul primitive + * Fixed performance of matmul primitive when fused with bias + update and sum + * Fixed a bug in matmul primitive when writing to non-contiguous + destination buffer +- Add upstream patch for GCC11 support + * 0001-common-gpu-include-thread-and-limit-headers-to-fix-G.patch + +------------------------------------------------------------------- +Thu May 27 08:10:13 UTC 2021 - Jan Engelhardt <jeng...@inai.de> + +- Update descriptions. + +------------------------------------------------------------------- +Wed May 26 13:29:27 UTC 2021 - Guillaume GARDET <guillaume.gar...@opensuse.org> + +- Update to 2.2.2, changes: + * Fixed performance regression in fp32 forward inner product for + shapes with number of output channels equal to 1 for processors + with Intel AVX-512 support (714b1fd) + * Fixed performance regression in forward convolutions with groups + for processors with Intel AVX-512 support(3555d4a) + * Removed -std=c++11 build flag for DPC++ headers (1fcb867) + * Fixed buffer access in initializing workspace in RNN + implementation on GPU (9b03091) + * Fixed fix a bug in convolution with 1x1 kernel and mixed + strides on processors with Intel AVX-512 support (d0b3e3f) + * Used getauxval for Linux to get CPU features on for AArch64 + systems (25c4cea) + * Added -fp-model=precise build flag for DPC++ code (3e40e5e) + * Fixed out-of-bounds writes in elementwise primitive on + Intel Processor Graphics (bcf823c) +- Fix build with Arm Compute Library: + * onednn-1045.patch + +------------------------------------------------------------------- Old: ---- onednn-2.2.1.tar.gz New: ---- 0001-common-gpu-include-thread-and-limit-headers-to-fix-G.patch oneDNN-2.2.3.tar.gz onednn-1045.patch ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Other differences: ------------------ ++++++ onednn.spec ++++++ --- /var/tmp/diff_new_pack.1tK6MF/_old 2021-06-04 22:43:28.263123166 +0200 +++ /var/tmp/diff_new_pack.1tK6MF/_new 2021-06-04 22:43:28.267123170 +0200 @@ -31,12 +31,16 @@ %define libname libdnnl2 Name: onednn -Version: 2.2.1 +Version: 2.2.3 Release: 0 -Summary: Intel(R) Math Kernel Library for Deep Neural Networks +Summary: Intel Math Kernel Library for Deep Neural Networks License: Apache-2.0 URL: https://01.org/onednn -Source0: https://github.com/oneapi-src/oneDNN/archive/v%{version}/%{name}-%{version}.tar.gz +Source0: https://github.com/oneapi-src/oneDNN/archive/v%{version}/oneDNN-%{version}.tar.gz +# PATCH-FIX-UPSTREAM onednn-1045.patch -- https://github.com/oneapi-src/oneDNN/pull/1045 +Patch0: onednn-1045.patch +# PATCH-FIX-UPSTREAM 0001-common-gpu-include-thread-and-limit-headers-to-fix-G.patch +Patch1: 0001-common-gpu-include-thread-and-limit-headers-to-fix-G.patch BuildRequires: cmake BuildRequires: doxygen BuildRequires: fdupes @@ -57,18 +61,18 @@ Provides: oneDNN = %{version} %description -Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN) is an +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. %package -n benchdnn -Summary: Header files of Intel(R) Math Kernel Library +Summary: Header files of Intel Math Kernel Library Requires: %{libname} = %{version} %description -n benchdnn -Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN) is an +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 @@ -77,43 +81,42 @@ This package only includes the benchmark utility including its input files. %package devel -Summary: Header files of Intel(R) Math Kernel Library +Summary: Header files of Intel Math Kernel Library Requires: %{libname} = %{version} Provides: mkl-dnn-devel = %{version} Obsoletes: mkl-dnn-devel <= %{version} Provides: oneDNN-devel = %{version} %description devel -Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN) is an +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(R) MKL-DNN. +with the Intel MKL-DNN. %package doc -Summary: Reference documentation for the Intel(R) Math Kernel Library +Summary: Reference documentation for the Intel Math Kernel Library BuildArch: noarch %description doc -The reference documentation for the Intel(R) Math Kernel Library can be installed +The reference documentation for the Intel Math Kernel Library can be installed with this package. %package -n %{libname} -Summary: Header files of Intel(R) Math Kernel Library +Summary: Header files of Intel Math Kernel Library %description -n %{libname} -Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN) is an +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. %prep -%setup -q -n oneDNN-%{version} -%autopatch -p1 +%autosetup -p1 -n oneDNN-%{version} %build %cmake \ @@ -167,6 +170,7 @@ %{_datadir}/benchdnn %files devel +%doc README.md %{_includedir}/mkl-dnn %{_includedir}/mkldnn*.h* %{_includedir}/dnnl*.h* @@ -185,7 +189,6 @@ %files -n %{libname} %license LICENSE -%doc README.md %{_libdir}/libdnnl.so.* %{_libdir}/libmkldnn.so.* ++++++ 0001-common-gpu-include-thread-and-limit-headers-to-fix-G.patch ++++++ >From cfbefd8d744d4cdcdf3dd2f18576f487b36911b6 Mon Sep 17 00:00:00 2001 From: Denis Samoilov <denis.samoy...@intel.com> Date: Fri, 2 Apr 2021 19:46:22 -0700 Subject: [PATCH] common, gpu: include thread and limit headers to fix GCC 11 build issues --- src/common/primitive_cache.hpp | 1 + src/gpu/jit/ngen/ngen_auto_swsb.hpp | 1 + 2 files changed, 2 insertions(+) diff --git a/src/common/primitive_cache.hpp b/src/common/primitive_cache.hpp index 73cb1224f..05a3e53e5 100644 --- a/src/common/primitive_cache.hpp +++ b/src/common/primitive_cache.hpp @@ -20,6 +20,7 @@ #include <future> #include <list> #include <memory> +#include <thread> #include <unordered_map> #include "c_types_map.hpp" diff --git a/src/gpu/jit/ngen/ngen_auto_swsb.hpp b/src/gpu/jit/ngen/ngen_auto_swsb.hpp index de3417af3..62ef2a571 100644 --- a/src/gpu/jit/ngen/ngen_auto_swsb.hpp +++ b/src/gpu/jit/ngen/ngen_auto_swsb.hpp @@ -33,6 +33,7 @@ #include <list> #include <map> +#include <limits> namespace ngen { namespace autoswsb { -- 2.26.2 ++++++ onednn-1045.patch ++++++ >From a94acd4e2dfaf51552dd2a60b059df1c1f14e452 Mon Sep 17 00:00:00 2001 From: Alexandre Truong <alexandre.tru...@arm.com> Date: Wed, 28 Apr 2021 10:32:35 +0100 Subject: [PATCH] cpu: aarch64: missing include for arm_compute::Scheduler --- src/cpu/aarch64/acl_indirect_gemm_convolution.hpp | 1 + 1 file changed, 1 insertion(+) diff --git a/src/cpu/aarch64/acl_indirect_gemm_convolution.hpp b/src/cpu/aarch64/acl_indirect_gemm_convolution.hpp index 86d2bed73..040311f8c 100644 --- a/src/cpu/aarch64/acl_indirect_gemm_convolution.hpp +++ b/src/cpu/aarch64/acl_indirect_gemm_convolution.hpp @@ -26,6 +26,7 @@ #include "arm_compute/runtime/FunctionDescriptors.h" #include "arm_compute/runtime/NEON/NEFunctions.h" +#include "arm_compute/runtime/Scheduler.h" namespace dnnl { namespace impl {
