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.

test/unit/nvrtc/kernel/thread/testbed_kernel.h

@@ -0,0 +1,70 @@
+/***************************************************************************************************
+ * Copyright (c) 2017-2019, NVIDIA CORPORATION.  All rights reserved.
+ *
+ * Redistribution and use in source and binary forms, with or without modification, are permitted
+ * provided that the following conditions are met:
+ *     * Redistributions of source code must retain the above copyright notice, this list of
+ *       conditions and the following disclaimer.
+ *     * Redistributions in binary form must reproduce the above copyright notice, this list of
+ *       conditions and the following disclaimer in the documentation and/or other materials
+ *       provided with the distribution.
+ *     * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used
+ *       to endorse or promote products derived from this software without specific prior written
+ *       permission.
+ *
+ * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
+ * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
+ * FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE
+ * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
+ * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
+ * OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
+ * STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+ * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+ *
+ **************************************************************************************************/
+/*! \file
+    \brief Unit tests for thread-level GEMM
+*/
+
+#pragma once
+
+#include "cutlass/array.h"
+
+namespace test {
+namespace nvrtc {
+namespace kernel {
+namespace thread {
+
+/////////////////////////////////////////////////////////////////////////////////////////////////
+
+/// Thread-level matrix multiply-accumulate
+template <typename Mma>
+__global__ void testbed_kernel(
+  typename Mma::ElementC *D,
+  typename Mma::ElementA const *A,
+  typename Mma::ElementB const *B,
+  typename Mma::ElementC const *C) {
+
+  auto ptr_D = reinterpret_cast<cutlass::Array<typename Mma::ElementC, Mma::Shape::kMN> *>(D);
+  auto ptr_A = reinterpret_cast<cutlass::Array<typename Mma::ElementA, Mma::Shape::kMK> const *>(A);
+  auto ptr_B = reinterpret_cast<cutlass::Array<typename Mma::ElementB, Mma::Shape::kKN> const *>(B);
+  auto ptr_C = reinterpret_cast<cutlass::Array<typename Mma::ElementC, Mma::Shape::kMN> const *>(C);
+
+  Mma mma;
+
+  auto a = *ptr_A;
+  auto b = *ptr_B;
+  auto c = *ptr_C;
+
+  cutlass::Array<typename Mma::ElementC, Mma::Shape::kMN> d;
+
+  mma(d, a, b, c);
+
+  *ptr_D = d;
+}
+
+}
+}
+}
+}
+