The comparison between cublaslt and deepgemm in test_fp8.py is unaligned

[Insideyyy]

It's great that PR #198 added cublas implementation to test_fp8.py, so we can directly observe the performance differences.
That said, I noticed the cublas implementation uses tensorwise scaling(cublas default behavior) instead of blockwise scaling, which makes the comparison with deepgemm less fair and potentially misleading.
Would it be possible to align the scaling strategy? I suppose cublas currently has supported the blockwise scaling strategy same with deepgemm: https://docs.nvidia.com/cuda/cublas/#element-1d-and-128x128-2d-block-scaling-for-fp8-data-types