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Why, after using OneDNN, did I find that the GEMM used in the call stack extracted with perf is arm_gemm from ARM Compute instead of BRGEMM from OneDNN?
#2256
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nanzh-19 opened this issue
Sep 26, 2024
· 0 comments
When I run TF Serving on an x64 machine, I notice that TensorFlow uses brgemm_matmul_t for inference, while on an ARM architecture machine, it uses arm_gemm. How can I also use brgemm_matmul on ARM, as it provides better performance?
The text was updated successfully, but these errors were encountered:
When I run TF Serving on an x64 machine, I notice that TensorFlow uses brgemm_matmul_t for inference, while on an ARM architecture machine, it uses arm_gemm. How can I also use brgemm_matmul on ARM, as it provides better performance?
The text was updated successfully, but these errors were encountered: