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@ -27,7 +27,8 @@ in CUDA C++"](https://devblogs.nvidia.com/parallelforall/cutlass-linear-algebra-
![ALT](/media/cutlass-performance-plot.png "Relative performance of CUTLASS and cuBLAS for large matrices") ![ALT](/media/cutlass-performance-plot.png "Relative performance of CUTLASS and cuBLAS for large matrices")
CUTLASS is very efficient, with performance comparable to cuBLAS for scalar GEMM CUTLASS primitives are very efficient. When used to construct device-wide GEMM kernels,
they exhibit performance comparable to cuBLAS for scalar GEMM
computations. The above figure shows CUTLASS performance relative to cuBLAS computations. The above figure shows CUTLASS performance relative to cuBLAS
for large matrix dimensions (M=10240, N=K=4096) running on an NVIDIA Tesla V100 GPU for large matrix dimensions (M=10240, N=K=4096) running on an NVIDIA Tesla V100 GPU
when compiled with CUDA 9.0. when compiled with CUDA 9.0.