CUTLASS 2.0 (#62)

CUTLASS 2.0

Substantially refactored for

- Better performance, particularly for native Turing Tensor Cores
- Robust and durable templates spanning the design space
- Encapsulated functionality embodying modern C++11 programming techniques
- Optimized containers and data types for efficient, generic, portable device code

Updates to:
- Quick start guide
- Documentation
- Utilities
- CUTLASS Profiler

Native Turing Tensor Cores
- Efficient GEMM kernels targeting Turing Tensor Cores
- Mixed-precision floating point, 8-bit integer, 4-bit integer, and binarized operands

Coverage of existing CUTLASS functionality:
- GEMM kernels targeting CUDA and Tensor Cores in NVIDIA GPUs
- Volta Tensor Cores through native mma.sync and through WMMA API
- Optimizations such as parallel reductions, threadblock rasterization, and intra-threadblock reductions
- Batched GEMM operations
- Complex-valued GEMMs

Note: this commit and all that follow require a host compiler supporting C++11 or greater.

docs/search/searchdata.js

@@ -1,16 +1,16 @@
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-  0: "_abcdefghiklmnoprstuvwyz~",
-  1: "abcdefghiklmnprstuvwz",
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+  1: "abcdefghiklmnoprstuvwx",
   2: "c",
-  3: "bcdfghiklmnprstvwz",
-  4: "_abcdefghiklmnoprstuvwz~",
-  5: "abcdefgiklmnoprstvw",
-  6: "abcdefgiklmnoprstvwy",
-  7: "k",
-  8: "abkmov",
+  3: "abcdefghiklmnoprstvw",
+  4: "_abcdefghiklmnopqrstuvw~",
+  5: "abcdefghiklmnoprstuvw",
+  6: "abcdefghiklmnoprstuvwy",
+  7: "cfgklmnos",
+  8: "gikrsuv",
   9: "_cns",
-  10: "filpt"
+  10: "p"
 };
 
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