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+/***************************************************************************************************
+ * Copyright (c) 2017-2018, 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 Specialization implementing multiply-add operation on half-precision floating point
+   fragments.
+*/
+#pragma once
+
+#include <cutlass/fragment.h>
+
+#include <cutlass/gemm/thread_multiply_add.h>
+
+namespace cutlass {
+namespace gemm {
+
+////////////////////////////////////////////////////////////////////////////////////////////////////
+
+/// Template performing matrix multiply-add operation within a thread
+template <typename AccumulatorsPerThread_, typename ThreadsPerWarp_>
+struct ThreadMultiplyAdd<AccumulatorsPerThread_, ThreadsPerWarp_, half, half, half> {
+  /// The shape of the instruction.
+  typedef Shape<1, 1, 2, 1> InstructionShape;
+  /// The number of accumulators per thread.
+  typedef AccumulatorsPerThread_ AccumulatorsPerThread;
+  /// The number of threads per warp.
+  typedef ThreadsPerWarp_ ThreadsPerWarp;
+  /// The number of accumulators per warp.
+  typedef typename ShapeMul<AccumulatorsPerThread, ThreadsPerWarp>::Shape AccumulatorsPerWarp;
+  /// The type for A.
+  typedef half ScalarA;
+  /// The fragment for A.
+  typedef Fragment<ScalarA, AccumulatorsPerThread::kW> FragmentA;
+  /// The type for B.
+  typedef half ScalarB;
+  /// The fragment for B.
+  typedef Fragment<ScalarB, AccumulatorsPerThread::kH> FragmentB;
+  /// The type for C and D.
+  typedef half ScalarC;
+  /// The accumulators.
+  typedef Fragment<half, AccumulatorsPerThread::kH * AccumulatorsPerThread::kW> Accumulators;
+
+  /// Make sure there's an even number of elements in both dimensions.
+  static_assert(AccumulatorsPerThread::kH % 2 == 0, "Invalid size");
+  static_assert(AccumulatorsPerThread::kW % 2 == 0, "Invalid size");
+
+  /// Ctor.
+  CUTLASS_DEVICE ThreadMultiplyAdd() {}
+
+  /// Multiply : d = a*b + c.
+  CUTLASS_DEVICE void multiply_add(FragmentA const& a,
+                                   FragmentB const& b,
+                                   Accumulators const& c,
+                                   Accumulators& d) {
+#if defined(__CUDACC__) && __CUDA_ARCH__ >= 530
+    // The inputs.
+    __half2 const* a_half2 = reinterpret_cast<__half2 const*>(&a[0]);
+    __half2 const* b_half2 = reinterpret_cast<__half2 const*>(&b[0]);
+    __half2 const* c_half2 = reinterpret_cast<__half2 const*>(&c[0]);
+
+    // The output.
+    __half2* d_half2 = reinterpret_cast<__half2*>(&d[0]);
+
+    for (int j = 0; j < AccumulatorsPerThread::kH / 2; ++j) {
+      for (int i = 0; i < AccumulatorsPerThread::kW / 2; ++i) {
+        // The offsets in the output fragment.
+        int const k0 = (2 * j + 0) * (AccumulatorsPerThread::kW / 2) + i;
+        int const k1 = (2 * j + 1) * (AccumulatorsPerThread::kW / 2) + i;
+
+        // Compute the product a[i] * b[j].H0_H0.
+        d_half2[k0] = __hfma2(a_half2[i], __low2half2(b_half2[j]), c_half2[k0]);
+        // Compute the product a[i] * b[j].H1_H1.
+        d_half2[k1] = __hfma2(a_half2[i], __high2half2(b_half2[j]), c_half2[k1]);
+      }
+    }
+#endif
+  }
+};
+
+////////////////////////////////////////////////////////////////////////////////////////////////////
+
+}  // namespace gemm
+}  // namespace cutlass