Improve performance of CUDA dot implementation
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@ -46,7 +46,7 @@ CUDAStream<T>::CUDAStream(const unsigned int ARRAY_SIZE, const int device_index)
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array_size = ARRAY_SIZE;
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// Allocate the host array for partial sums for dot kernels
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sums = (T*)malloc(sizeof(T) * (ARRAY_SIZE/TBSIZE));
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sums = (T*)malloc(sizeof(T) * DOT_NUM_BLOCKS);
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// Check buffers fit on the device
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cudaDeviceProp props;
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@ -61,7 +61,7 @@ CUDAStream<T>::CUDAStream(const unsigned int ARRAY_SIZE, const int device_index)
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check_error();
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cudaMalloc(&d_c, ARRAY_SIZE*sizeof(T));
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check_error();
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cudaMalloc(&d_sum, (ARRAY_SIZE/TBSIZE)*sizeof(T));
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cudaMalloc(&d_sum, DOT_NUM_BLOCKS*sizeof(T));
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check_error();
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}
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@ -171,16 +171,18 @@ void CUDAStream<T>::triad()
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}
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template <class T>
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__global__ void dot_kernel(const T * a, const T * b, T * sum)
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__global__ void dot_kernel(const T * a, const T * b, T * sum, unsigned int array_size)
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{
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extern __shared__ __align__(sizeof(T)) unsigned char smem[];
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T *tb_sum = reinterpret_cast<T*>(smem);
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const int i = blockDim.x * blockIdx.x + threadIdx.x;
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int i = blockDim.x * blockIdx.x + threadIdx.x;
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const size_t local_i = threadIdx.x;
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tb_sum[local_i] = a[i] * b[i];
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tb_sum[local_i] = 0.0;
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for (; i < array_size; i += blockDim.x*gridDim.x)
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tb_sum[local_i] += a[i] * b[i];
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for (int offset = blockDim.x / 2; offset > 0; offset /= 2)
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{
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@ -198,14 +200,14 @@ __global__ void dot_kernel(const T * a, const T * b, T * sum)
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template <class T>
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T CUDAStream<T>::dot()
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{
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dot_kernel<<<array_size/TBSIZE, TBSIZE, sizeof(T)*TBSIZE>>>(d_a, d_b, d_sum);
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dot_kernel<<<DOT_NUM_BLOCKS, TBSIZE, sizeof(T)*TBSIZE>>>(d_a, d_b, d_sum, array_size);
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check_error();
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cudaMemcpy(sums, d_sum, (array_size/TBSIZE)*sizeof(T), cudaMemcpyDeviceToHost);
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cudaMemcpy(sums, d_sum, DOT_NUM_BLOCKS*sizeof(T), cudaMemcpyDeviceToHost);
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check_error();
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T sum = 0.0;
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for (int i = 0; i < (array_size/TBSIZE); i++)
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for (int i = 0; i < DOT_NUM_BLOCKS; i++)
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sum += sums[i];
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return sum;
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@ -16,6 +16,7 @@
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#define IMPLEMENTATION_STRING "CUDA"
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#define TBSIZE 1024
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#define DOT_NUM_BLOCKS 256
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template <class T>
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class CUDAStream : public Stream<T>
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