[FEA] transpose in epilogue/prologue

Now I'm using cutlass in my project. I found that some cases have constraints to the layout, such as input matrix A and output matrix C should be row major. These kinds of assumption limit the feasibility to add the cutlass gemm kernel directly in my project without transpose kernels. If cutlass can provide examples to show how to fuse the transpose in the epilogue and "prologue" phases, overhead of the transpose kernels will be eliminated.

I did some tests to show the overhead of adding transpose kernels of an MxN matrix on A100-80G:
m = 8, n = 4096, latency = 8.40 us
m = 8, n = 1024, latency = 7.03 us
m = 8, n = 14336, latency = 7.12 us
m = 8, n = 4096, latency = 6.98 us
m = 32, n = 4096, latency = 6.97 us
m = 32, n = 1024, latency = 6.98 us
m = 32, n = 14336, latency = 8.26 us
m = 32, n = 4096, latency = 8.35 us
m = 256, n = 4096, latency = 15.65 us
m = 256, n = 1024, latency = 7.16 us
m = 256, n = 14336, latency = 46.49 us
m = 256, n = 4096, latency = 15.83 us
m = 512, n = 4096, latency = 28.82 us
m = 512, n = 1024, latency = 10.31 us
m = 512, n = 14336, latency = 92.73 us
m = 512, n = 4096, latency = 28.88 us

m = 4096, n = 8, latency = 7.07 us
m = 1024, n = 8, latency = 8.18 us
m = 14336, n = 8, latency = 7.52 us
m = 4096, n = 8, latency = 8.34 us
m = 4096, n = 32, latency = 8.35 us
m = 1024, n = 32, latency = 7.83 us
m = 14336, n = 32, latency = 9.65 us
m = 4096, n = 32, latency = 8.34 us
m = 4096, n = 256, latency = 15.90 us
m = 1024, n = 256, latency = 8.18 us
m = 14336, n = 256, latency = 46.24 us
m = 4096, n = 256, latency = 15.90 us
m = 4096, n = 512, latency = 26.69 us
m = 1024, n = 512, latency = 10.29 us
m = 14336, n = 512, latency = 88.09 us
m = 4096, n = 512, latency = 26.65 us

It can be seen that when m or n is large, e.g. 14336, the transpose kernel hurts the e2e performance of a model.

The issue names no files, entry points, or tests. Start by locating CUTLASS GEMM epilogue and prologue examples, then review how layouts are constrained and how the A100 transpose benchmarks were measured. Done should include documented examples showing fused transpose handling and evidence that the separate transpose overhead is addressed.