uxlfoundation/oneDNN v3.8.2

on GitHub

This is a patch release containing the following changes to v3.8.1:

• Fixed performance regression for f32 convolution primitive on processors with Intel AVX-512 instruction set support (5f3af68)
• Introduced support for f16 destination in int8 matmul and int8 inner product on x64 CPUs (53fd12a, 22e252c, f5b2d7f, e4e2f1c)
• Improved RNN primitive performance on processors with Intel AVX2 instruction set support (71e5d81, eb27db2, dd4e627, ff134e0, 5a86c1f, e9395ae)
• Improved fp32 matmul performance on processors with Intel AVX-512 instruction set support (1119339)
• Fixed segmentation fault in f32 binary primitive with broadcast on x64 processors (2082e98)
• Fixed correctness issue in f64 convolution weight gradient with bias on Intel Arc GPUs (a00bfab)
• Updated spdlog component to version 1.15.3 (dbb3629)
• Fixed potential undefined behavior in convolution on Intel GPUs (5ac3e31)
• Fixed segmentation fault in convolution implementation with trivial filter on Intel CPUs (908c5fc, f0a0eee)
• Fixed segmentation fault in f16 convolution with odd dimensions on processors with Intel AVX10.1 instruction set support (78d6835)
• Improved convolution primitive descriptor creation time on x64 processors (e9c5366, fd9dc58, f1d038e)
• Fixed performance regression in f16 matmul with int4 weights on Intel Arc Graphics B-series (38d761b)
• Improved bf16 matmul performance on processors with Intel AMX instruction set support (0887aec)
• Fixed correctness issue in f32 RNN primitive on processors with Intel AMX instruction set support (460a014)