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In TensorFlow version 2.16 (and later), the convolution operation implementation for FP32 data type in oneDNN was changed from gemm:acl to gemm:ref. However, this change has resulted in performance degradation compared to TensorFlow version 2.15, where gemm:acl was used.
System Information:
TensorFlow Version: 2.16
Previous Working Version: 2.15
oneDNN Version: 3.2.1
Hardware: Aarch64
Operating System: Ubuntu 22.04
Issue Summary:
In TensorFlow 2.15, the convolution operation for FP32 data type was routed through gemm:acl in oneDNN, which provided better performance.
In TensorFlow 2.16 (and later), the implementation was changed to use gemm:ref, leading to a noticeable performance drop.
The text was updated successfully, but these errors were encountered:
In TensorFlow version 2.16 (and later), the convolution operation implementation for FP32 data type in oneDNN was changed from gemm:acl to gemm:ref. However, this change has resulted in performance degradation compared to TensorFlow version 2.15, where gemm:acl was used.
System Information:
Issue Summary:
The text was updated successfully, but these errors were encountered: