Fix README (#1658)
* Fix README * Improve README --------- Co-authored-by: Haicheng Wu <57973641+hwu36@users.noreply.github.com>
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In addition to GEMMs, CUTLASS implements high-performance convolution via the implicit GEMM algorithm. Implicit GEMM is the formulation of a convolution operation as a GEMM thereby taking advantage of CUTLASS's modular GEMM pipeline. This allows CUTLASS to build convolutions by reusing highly-optimized GEMM components.
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# What's New in CUTLASS 3.6
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CUTLASS 3.6.0 is an update to CUTLASS adding:
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@ -179,11 +179,13 @@ $ make test_unit_gemm_warp -j
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To minimize compilation time, specific GPU architectures can be enabled via the CMake command,
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selected by [CUDA Compute Capability.](https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#compute-capabilities)
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**NVIDIA Ampere Architecture.**
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**NVIDIA Hopper Architecture.**
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```bash
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$ cmake .. -DCUTLASS_NVCC_ARCHS=90a # compiles for NVIDIA Hopper GPU architecture
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```
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**NVIDIA Ampere Architecture.**
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```bash
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$ cmake .. -DCUTLASS_NVCC_ARCHS=80 # compiles for NVIDIA Ampere GPU architecture
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```
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