Vectorized the evaluation of tensor expression (using SSE, AVX, NEON, ...)

Added the ability to parallelize the evaluation of a tensor expression over multiple cpu cores.
Added the ability to offload the evaluation of a tensor expression to a GPU.

unsupported/Eigen/CXX11/src/Tensor/TensorDevice.h

@@ -0,0 +1,83 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CXX11_TENSOR_TENSOR_DEVICE_H
+#define EIGEN_CXX11_TENSOR_TENSOR_DEVICE_H
+
+namespace Eigen {
+
+/** \class TensorDevice
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Pseudo expression providing an operator = that will evaluate its argument
+  * on the specified computing 'device' (GPU, thread pool, ...)
+  *
+  * Example:
+  *    C.device(EIGEN_GPU) = A + B;
+  *
+  * Todo: thread pools.
+  * Todo: operator +=, -=, *= and so on.
+  */
+
+template <typename ExpressionType, typename DeviceType> class TensorDevice {
+  public:
+    TensorDevice(const DeviceType& device, ExpressionType& expression) : m_device(device), m_expression(expression) {}
+
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE TensorDevice& operator=(const OtherDerived& other) {
+      internal::TensorAssign<ExpressionType, const OtherDerived>::run(m_expression, other);
+      return *this;
+    }
+
+  protected:
+    const DeviceType& m_device;
+    ExpressionType& m_expression;
+};
+
+
+#ifdef EIGEN_USE_THREADS
+template <typename ExpressionType> class TensorDevice<ExpressionType, ThreadPoolDevice> {
+  public:
+    TensorDevice(const ThreadPoolDevice& device, ExpressionType& expression) : m_device(device), m_expression(expression) {}
+
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE TensorDevice& operator=(const OtherDerived& other) {
+      internal::TensorAssignMultiThreaded<ExpressionType, const OtherDerived>::run(m_expression, other, m_device);
+      return *this;
+    }
+
+  protected:
+    const ThreadPoolDevice& m_device;
+    ExpressionType& m_expression;
+};
+#endif
+
+
+#ifdef EIGEN_USE_GPU
+template <typename ExpressionType> class TensorDevice<ExpressionType, GpuDevice>
+{
+  public:
+    TensorDevice(const GpuDevice& device, ExpressionType& expression) : m_device(device), m_expression(expression) {}
+
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE TensorDevice& operator=(const OtherDerived& other) {
+      internal::TensorAssignGpu<ExpressionType, const OtherDerived>::run(m_expression, other, m_device);
+      return *this;
+    }
+
+  protected:
+    const GpuDevice& m_device;
+    ExpressionType& m_expression;
+};
+#endif
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_DEVICE_H