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// 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_DEFAULT_H
#define EIGEN_CXX11_TENSOR_TENSOR_DEVICE_DEFAULT_H
#include "./InternalHeaderCheck.h"
namespace Eigen {
// Default device for the machine (typically a single cpu core)
struct DefaultDevice {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void* allocate(size_t num_bytes) const {
return internal::aligned_malloc(num_bytes);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void deallocate(void* buffer) const {
internal::aligned_free(buffer);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void* allocate_temp(size_t num_bytes) const {
return allocate(num_bytes);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void deallocate_temp(void* buffer) const {
deallocate(buffer);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpy(void* dst, const void* src, size_t n) const {
::memcpy(dst, src, n);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpyHostToDevice(void* dst, const void* src, size_t n) const {
memcpy(dst, src, n);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpyDeviceToHost(void* dst, const void* src, size_t n) const {
memcpy(dst, src, n);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memset(void* buffer, int c, size_t n) const {
::memset(buffer, c, n);
}
template<typename T>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void fill(T* begin, T* end, const T& value) const {
#ifdef EIGEN_GPU_COMPILE_PHASE
// std::fill is not a device function, so resort to simple loop.
for (T* it = begin; it != end; ++it) {
*it = value;
}
#else
std::fill(begin, end, value);
#endif
}
template<typename Type>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Type get(Type data) const {
return data;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE size_t numThreads() const {
#if !defined(EIGEN_GPU_COMPILE_PHASE)
// Running on the host CPU
return 1;
#elif defined(EIGEN_HIP_DEVICE_COMPILE)
// Running on a HIP device
return 64;
#else
// Running on a CUDA device
return 32;
#endif
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE size_t firstLevelCacheSize() const {
#if !defined(EIGEN_GPU_COMPILE_PHASE) && !defined(SYCL_DEVICE_ONLY)
// Running on the host CPU
return l1CacheSize();
#elif defined(EIGEN_HIP_DEVICE_COMPILE)
// Running on a HIP device
return 48*1024; // FIXME : update this number for HIP
#else
// Running on a CUDA device, return the amount of shared memory available.
return 48*1024;
#endif
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE size_t lastLevelCacheSize() const {
#if !defined(EIGEN_GPU_COMPILE_PHASE) && !defined(SYCL_DEVICE_ONLY)
// Running single threaded on the host CPU
return l3CacheSize();
#elif defined(EIGEN_HIP_DEVICE_COMPILE)
// Running on a HIP device
return firstLevelCacheSize(); // FIXME : update this number for HIP
#else
// Running on a CUDA device
return firstLevelCacheSize();
#endif
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE int majorDeviceVersion() const {
#if !defined(EIGEN_GPU_COMPILE_PHASE)
// Running single threaded on the host CPU
// Should return an enum that encodes the ISA supported by the CPU
return 1;
#elif defined(EIGEN_HIP_DEVICE_COMPILE)
// Running on a HIP device
// return 1 as major for HIP
return 1;
#else
// Running on a CUDA device
return EIGEN_CUDA_ARCH / 100;
#endif
}
};
} // namespace Eigen
#endif // EIGEN_CXX11_TENSOR_TENSOR_DEVICE_DEFAULT_H