Comments (1)
Thanks for the interest @akote123
- Adding @Xia-Weiwen for ipex part. I believe that libxsmm ukernels are used only for some complex fused patterns. There is ongoing work with ipex team to migrate to the new oneDNN brgemm APIs.
- Not sure I understand the question. @jgong can better address the details about pytorch internals.
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Related Issues (20)
- question about matmul_perf example HOT 2
- Information regarding threading backend in oneDNN HOT 1
- could not create a primitive descriptor iterator HOT 5
- cpu: s390x: build fails with saturate was not declared in this scope HOT 7
- Enabling onednn Graph API from framework level HOT 4
- Conditions for Running brgemm_convolution_fwd_t and jit_avx512_common_convolution_fwd_t in oneDNN HOT 3
- oneDNN with Nvidia GPU supprt
- batchnorm requires consistent in- and output mem format_tags HOT 4
- Build fail with CPU_RUNTIME=SEQ and graph compiler backend HOT 4
- OneDNN graph APi for LLM generation HOT 7
- dnnl_sgemm occurs segmentation fault with special size HOT 2
- SSE41 kernels are broken HOT 5
- Generic OpenCL kernels are broken HOT 2
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- Convolution Test Failures and Skips on AArch64 HOT 2
- Can't create engine in amd backend. HOT 3
- AMX and VNNI perform nearly the same in IP primitives HOT 1
- Heuristics for operations workload distribution for matrix multiplication based on number of threads HOT 2
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