CUTLASS 2.3 initial commit (#134)

CUTLASS 2.3 adds GEMMs targeting Sparse Tensor Cores on the NVIDIA Ampere Architecture, fast SGEMM, and small matrix classes, bug fixes, and performance enhancements.

examples/11_planar_complex_array/planar_complex_array.cu

@@ -48,7 +48,7 @@
   To build strictly the planar complex kernels needed for general application, execute the following
   CMake command in an empty build directory.
 
-    $ cmake .. -DCUTLASS_NVCC_ARCHS="70;75" \
+    $ cmake .. -DCUTLASS_NVCC_ARCHS="70;75;80" \
       -DCUTLASS_LIBRARY_KERNELS=cutlass_tensorop_*gemm_planar_complex
 
   This builds all planar complex GEMM variants for Volta and Turing architectures.
@@ -57,7 +57,7 @@
   specified as follows. This only builds planar complex GEMMs targeting Tensor Cores for
   the 'CN' layout configuration (conjugate A operand with both A and B as column-major).
 
-    $ cmake .. -DCUTLASS_NVCC_ARCHS="70;75" \
+    $ cmake .. -DCUTLASS_NVCC_ARCHS="70;75;80" \
       -DCUTLASS_LIBRARY_KERNELS=cutlass_tensorop_f16_s*gemm_planar_complex_array_f16*cn
 
     $ make 11_planar_complex_array
@@ -586,6 +586,11 @@ int main(int argc, char const **args) {
       return 0;
     }
   }
+  else {
+    // NVIDIA Ampere Architecture GPUs (SM80 and later) are fully supported on CUDA 11 Toolkit and beyond.
+    //
+    // fall through
+  }
 
   //
   // Parse options