148 lines
2.8 KiB
C++
148 lines
2.8 KiB
C++
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// Copyright (c) 2015-16 Tom Deakin, Simon McIntosh-Smith,
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// University of Bristol HPC
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//
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// For full license terms please see the LICENSE file distributed with this
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// source code
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#include "RAJAStream.hpp"
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using RAJA::forall;
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using RAJA::RangeSegment;
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template <class T>
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RAJAStream<T>::RAJAStream(const unsigned int ARRAY_SIZE, const int device_index)
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: array_size(ARRAY_SIZE)
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{
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RangeSegment seg(0, ARRAY_SIZE);
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index_set.push_back(seg);
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#ifdef RAJA_TARGET_CPU
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d_a = new T[ARRAY_SIZE];
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d_b = new T[ARRAY_SIZE];
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d_c = new T[ARRAY_SIZE];
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#else
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cudaMallocManaged((void**)&d_a, sizeof(T)*ARRAY_SIZE, cudaMemAttachGlobal);
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cudaMallocManaged((void**)&d_b, sizeof(T)*ARRAY_SIZE, cudaMemAttachGlobal);
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cudaMallocManaged((void**)&d_c, sizeof(T)*ARRAY_SIZE, cudaMemAttachGlobal);
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cudaDeviceSynchronize();
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#endif
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}
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template <class T>
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RAJAStream<T>::~RAJAStream()
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{
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#ifdef RAJA_TARGET_CPU
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delete[] d_a;
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delete[] d_b;
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delete[] d_c;
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#else
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cudaFree(d_a);
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cudaFree(d_b);
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cudaFree(d_c);
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#endif
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}
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template <class T>
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void RAJAStream<T>::write_arrays(
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const std::vector<T>& a, const std::vector<T>& b, const std::vector<T>& c)
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{
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std::copy(a.begin(), a.end(), d_a);
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std::copy(b.begin(), b.end(), d_b);
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std::copy(c.begin(), c.end(), d_c);
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}
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template <class T>
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void RAJAStream<T>::read_arrays(
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std::vector<T>& a, std::vector<T>& b, std::vector<T>& c)
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{
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std::copy(d_a, d_a + array_size, a.data());
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std::copy(d_b, d_b + array_size, b.data());
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std::copy(d_c, d_c + array_size, c.data());
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}
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template <class T>
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void RAJAStream<T>::copy()
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{
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T* a = d_a;
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T* c = d_c;
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forall<policy>(index_set, [=] RAJA_DEVICE (int index)
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{
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c[index] = a[index];
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});
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}
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template <class T>
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void RAJAStream<T>::mul()
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{
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T* b = d_b;
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T* c = d_c;
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const T scalar = startScalar;
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forall<policy>(index_set, [=] RAJA_DEVICE (int index)
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{
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b[index] = scalar*c[index];
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});
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}
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template <class T>
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void RAJAStream<T>::add()
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{
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T* a = d_a;
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T* b = d_b;
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T* c = d_c;
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forall<policy>(index_set, [=] RAJA_DEVICE (int index)
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{
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c[index] = a[index] + b[index];
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});
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}
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template <class T>
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void RAJAStream<T>::triad()
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{
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T* a = d_a;
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T* b = d_b;
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T* c = d_c;
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const T scalar = startScalar;
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forall<policy>(index_set, [=] RAJA_DEVICE (int index)
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{
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a[index] = b[index] + scalar*c[index];
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});
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}
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template <class T>
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T RAJAStream<T>::dot()
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{
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T* a = d_a;
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T* b = d_b;
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RAJA::ReduceSum<reduce_policy, T> sum(0.0);
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forall<policy>(index_set, [=] RAJA_DEVICE (int index)
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{
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sum += a[index] * b[index];
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});
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return T(sum);
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}
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void listDevices(void)
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{
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std::cout << "This is not the device you are looking for.";
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}
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std::string getDeviceName(const int device)
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{
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return "RAJA";
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}
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std::string getDeviceDriver(const int device)
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{
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return "RAJA";
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}
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template class RAJAStream<float>;
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template class RAJAStream<double>;
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