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@ -20,6 +20,9 @@ point (FP64) types. Furthermore, CUTLASS demonstrates CUDA's WMMA API for targe
the programmable, high-throughput _Tensor Cores_ provided by NVIDIA's Volta architecture
and beyond.
For more exposition, see our Parallel Forall blog post ["CUTLASS: Fast Linear Algebra
in CUDA C++"](https://devblogs.nvidia.com/parallelforall/cutlass-linear-algebra-cuda).
# Project Structure
CUTLASS is arranged as a header-only library with several example test programs
@ -56,7 +59,7 @@ transposititions. Be sure to specify your target architecture.
<s|d|h|i|w>gemm_<nn|nt|tn|tt>
[--help]
[--schmoo || --m=<height> --n=<width> --k=<depth>]
[--schmoo=<#schmoo-samples> || --m=<height> --n=<width> --k=<depth>]
[--i=<timing iterations>]
[--device=<device-id>]
[--alpha=<alpha> --beta=<beta>]