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When comparing PyTorch code with those generated using HIP kernels, the PyTorch code's inherent overhead can create an uneven comparison. We need to determine the extent of this overhead and explore potential strategies to mitigate it.
When comparing PyTorch code with those generated using HIP kernels, the PyTorch code's inherent overhead can create an uneven comparison. We need to determine the extent of this overhead and explore potential strategies to mitigate it.