428 lines
13 KiB
Plaintext
428 lines
13 KiB
Plaintext
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#include <iostream>
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#include <fstream>
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#include <vector>
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#include <chrono>
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#include <cfloat>
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#include <iomanip>
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#include <cmath>
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#include <cuda.h>
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#define DATATYPE double
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unsigned int ARRAY_SIZE = 50000000;
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unsigned int NTIMES = 10;
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size_t DATATYPE_SIZE = sizeof(double);
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bool useFloat = false;
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#define MIN(a,b) ((a) < (b)) ? (a) : (b)
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#define MAX(a,b) ((a) > (b)) ? (a) : (b)
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#define VERSION_STRING "0.0"
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void parseArguments(int argc, char *argv[]);
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std::string getDeviceName(int device);
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struct invaliddevice : public std::exception
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{
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virtual const char * what () const throw ()
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{
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return "Chosen device index is invalid";
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}
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};
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struct badntimes : public std::exception
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{
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virtual const char * what () const throw ()
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{
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return "Chosen number of times is invalid, must be >= 2";
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}
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};
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size_t sizes[4] = {
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2 * DATATYPE_SIZE * ARRAY_SIZE,
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2 * DATATYPE_SIZE * ARRAY_SIZE,
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3 * DATATYPE_SIZE * ARRAY_SIZE,
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3 * DATATYPE_SIZE * ARRAY_SIZE
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};
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void check_solution(void* a, void* b, void* c)
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{
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// Generate correct solution
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double golda = 1.0;
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double goldb = 2.0;
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double goldc = 0.0;
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float goldaf = 1.0;
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float goldbf = 2.0;
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float goldcf = 0.0;
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const double scalar = 3.0;
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const float scalarf = 3.0;
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for (unsigned int i = 0; i < NTIMES; i++)
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{
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// Double
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goldc = golda;
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goldb = scalar * goldc;
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goldc = golda + goldb;
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golda = goldb + scalar * goldc;
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// Float
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goldcf = goldaf;
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goldbf = scalarf * goldcf;
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goldcf = goldaf + goldbf;
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goldaf = goldbf + scalarf * goldcf;
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}
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// Calculate average error
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double erra = 0.0;
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double errb = 0.0;
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double errc = 0.0;
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for (unsigned int i = 0; i < ARRAY_SIZE; i++)
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{
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if (useFloat)
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{
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erra += fabsf(((float*)a)[i] - goldaf);
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errb += fabsf(((float*)b)[i] - goldbf);
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errc += fabsf(((float*)c)[i] - goldcf);
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}
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else
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{
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erra += fabs(((double*)a)[i] - (double)golda);
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errb += fabs(((double*)b)[i] - (double)goldb);
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errc += fabs(((double*)c)[i] - (double)goldc);
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}
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}
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erra /= (double)ARRAY_SIZE;
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errb /= (double)ARRAY_SIZE;
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errc /= (double)ARRAY_SIZE;
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double epsi;
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if (useFloat) epsi = 1.0E-6;
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else epsi = 1.0E-13;
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if (erra > epsi)
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std::cout
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<< "Validation failed on a[]. Average error " << erra
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<< std::endl;
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if (errb > epsi)
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std::cout
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<< "Validation failed on b[]. Average error " << errb
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<< std::endl;
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if (errc > epsi)
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std::cout
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<< "Validation failed on c[]. Average error " << errc
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<< std::endl;
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}
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template <typename T>
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__global__ void copy(const T * a, T * c)
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{
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const int i = blockDim.x * blockIdx.x + threadIdx.x;
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c[i] = a[i];
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}
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template <typename T>
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__global__ void mul(T * b, const T * c)
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{
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const T scalar = 3.0;
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const int i = blockDim.x * blockIdx.x + threadIdx.x;
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b[i] = scalar * c[i];
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}
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template <typename T>
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__global__ void add(const T * a, const T * b, T * c)
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{
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const int i = blockDim.x * blockIdx.x + threadIdx.x;
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c[i] = a[i] + b[i];
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}
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template <typename T>
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__global__ void triad(T * a, const T * b, const T * c)
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{
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const T scalar = 3.0;
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const int i = blockDim.x * blockIdx.x + threadIdx.x;
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a[i] = b[i] + scalar * c[i];
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}
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int deviceIndex = 0;
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int main(int argc, char *argv[])
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{
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// Print out run information
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std::cout
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<< "GPU-STREAM" << std::endl
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<< "Version: " << VERSION_STRING << std::endl
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<< "Implementation: CUDA" << std::endl << std::endl;
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if (ARRAY_SIZE % 1024 != 0)
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{
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unsigned int OLD_ARRAY_SIZE = ARRAY_SIZE;
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ARRAY_SIZE -= ARRAY_SIZE % 1024;
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std::cout
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<< "Warning: array size must divide 1024" << std::endl
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<< "Resizing array from " << OLD_ARRAY_SIZE
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<< " to " << ARRAY_SIZE << std::endl;
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}
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try
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{
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parseArguments(argc, argv);
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if (NTIMES < 2) throw badntimes();
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// Check device index is in range
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int count;
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cudaGetDeviceCount(&count);
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if (deviceIndex >= count) throw invaliddevice();
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cudaSetDevice(deviceIndex);
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// Print out device name
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std::cout << "Using CUDA device " << getDeviceName(deviceIndex) << std::endl;
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// Create host vectors
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void * h_a = malloc(ARRAY_SIZE*DATATYPE_SIZE);
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void * h_b = malloc(ARRAY_SIZE*DATATYPE_SIZE);
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void * h_c = malloc(ARRAY_SIZE*DATATYPE_SIZE);
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// Initilise arrays
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for (unsigned int i = 0; i < ARRAY_SIZE; i++)
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{
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if (useFloat)
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{
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((float*)h_a)[i] = 1.0;
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((float*)h_b)[i] = 2.0;
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((float*)h_c)[i] = 0.0;
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}
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else
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{
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((double*)h_a)[i] = 1.0;
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((double*)h_b)[i] = 2.0;
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((double*)h_c)[i] = 0.0;
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}
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}
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// Create device buffers
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void * d_a, * d_b, *d_c;
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cudaMalloc(&d_a, ARRAY_SIZE*DATATYPE_SIZE);
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cudaMalloc(&d_b, ARRAY_SIZE*DATATYPE_SIZE);
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cudaMalloc(&d_c, ARRAY_SIZE*DATATYPE_SIZE);
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// Copy host memory to device
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cudaMemcpy(d_a, h_a, ARRAY_SIZE*DATATYPE_SIZE, cudaMemcpyHostToDevice);
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cudaMemcpy(d_b, h_b, ARRAY_SIZE*DATATYPE_SIZE, cudaMemcpyHostToDevice);
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cudaMemcpy(d_c, h_c, ARRAY_SIZE*DATATYPE_SIZE, cudaMemcpyHostToDevice);
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// Make sure the copies are finished
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cudaDeviceSynchronize();
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// List of times
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std::vector< std::vector<double> > timings;
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// Declare timers
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std::chrono::high_resolution_clock::time_point t1, t2;
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// Main loop
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for (unsigned int k = 0; k < NTIMES; k++)
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{
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std::vector<double> times;
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t1 = std::chrono::high_resolution_clock::now();
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if (useFloat)
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copy<<<ARRAY_SIZE/1024, 1024>>>((float*)d_a, (float*)d_c);
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else
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copy<<<ARRAY_SIZE/1024, 1024>>>((double*)d_a, (double*)d_c);
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cudaDeviceSynchronize();
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t2 = std::chrono::high_resolution_clock::now();
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times.push_back(std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count());
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t1 = std::chrono::high_resolution_clock::now();
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if (useFloat)
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mul<<<ARRAY_SIZE/1024, 1024>>>((float*)d_b, (float*)d_c);
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else
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mul<<<ARRAY_SIZE/1024, 1024>>>((double*)d_b, (double*)d_c);
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cudaDeviceSynchronize();
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t2 = std::chrono::high_resolution_clock::now();
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times.push_back(std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count());
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t1 = std::chrono::high_resolution_clock::now();
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if (useFloat)
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add<<<ARRAY_SIZE/1024, 1024>>>((float*)d_a, (float*)d_b, (float*)d_c);
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else
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add<<<ARRAY_SIZE/1024, 1024>>>((double*)d_a, (double*)d_b, (double*)d_c);
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cudaDeviceSynchronize();
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t2 = std::chrono::high_resolution_clock::now();
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times.push_back(std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count());
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t1 = std::chrono::high_resolution_clock::now();
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if (useFloat)
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triad<<<ARRAY_SIZE/1024, 1024>>>((float*)d_a, (float*)d_b, (float*)d_c);
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else
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triad<<<ARRAY_SIZE/1024, 1024>>>((double*)d_a, (double*)d_b, (double*)d_c);
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cudaDeviceSynchronize();
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t2 = std::chrono::high_resolution_clock::now();
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times.push_back(std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count());
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timings.push_back(times);
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}
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// Check solutions
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cudaMemcpy(h_a, d_a, ARRAY_SIZE*DATATYPE_SIZE, cudaMemcpyDeviceToHost);
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cudaMemcpy(h_b, d_b, ARRAY_SIZE*DATATYPE_SIZE, cudaMemcpyDeviceToHost);
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cudaMemcpy(h_c, d_c, ARRAY_SIZE*DATATYPE_SIZE, cudaMemcpyDeviceToHost);
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check_solution(h_a, h_b, h_c);
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// Crunch results
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double min[4] = {DBL_MAX, DBL_MAX, DBL_MAX, DBL_MAX};
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double max[4] = {0.0, 0.0, 0.0, 0.0};
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double avg[4] = {0.0, 0.0, 0.0, 0.0};
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// Ignore first result
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for (unsigned int i = 1; i < NTIMES; i++)
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{
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for (int j = 0; j < 4; j++)
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{
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avg[j] += timings[i][j];
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min[j] = MIN(min[j], timings[i][j]);
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max[j] = MAX(max[j], timings[i][j]);
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}
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}
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for (int j = 0; j < 4; j++)
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avg[j] /= (double)(NTIMES-1);
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// Display results
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std::string labels[] = {"Copy", "Mul", "Add", "Triad"};
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std::cout
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<< std::left << std::setw(12) << "Function"
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<< std::left << std::setw(12) << "MBytes/sec"
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<< std::left << std::setw(12) << "Min (sec)"
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<< std::left << std::setw(12) << "Max"
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<< std::left << std::setw(12) << "Average"
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<< std::endl;
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for (int j = 0; j < 4; j++)
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{
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std::cout
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<< std::left << std::setw(12) << labels[j]
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<< std::left << std::setw(12) << 1.0E-06 * sizes[j]/min[j]
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<< std::left << std::setw(12) << min[j]
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<< std::left << std::setw(12) << max[j]
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<< std::left << std::setw(12) << avg[j]
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<< std::endl;
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}
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}
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catch (std::exception& e)
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{
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std::cerr
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<< "Error: "
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<< e.what()
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<< std::endl;
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}
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}
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std::string getDeviceName(int device)
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{
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struct cudaDeviceProp prop;
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cudaGetDeviceProperties(&prop, device);
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return std::string(prop.name);
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}
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int parseUInt(const char *str, unsigned int *output)
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{
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char *next;
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*output = strtoul(str, &next, 10);
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return !strlen(next);
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}
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int parseInt(const char *str, int *output)
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{
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char *next;
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*output = strtol(str, &next, 10);
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return !strlen(next);
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}
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void parseArguments(int argc, char *argv[])
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{
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for (int i = 1; i < argc; i++)
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{
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if (!strcmp(argv[i], "--list"))
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{
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// Get number of devices
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int count;
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cudaGetDeviceCount(&count);
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// Print device names
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if (count == 0)
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{
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std::cout << "No devices found." << std::endl;
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}
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else
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{
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std::cout << std::endl;
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std::cout << "Devices:" << std::endl;
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for (int i = 0; i < count; i++)
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{
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std::cout << i << ": " << getDeviceName(i) << std::endl;
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}
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std::cout << std::endl;
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}
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exit(0);
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}
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else if (!strcmp(argv[i], "--device"))
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{
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if (++i >= argc || !parseInt(argv[i], &deviceIndex))
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{
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std::cout << "Invalid device index" << std::endl;
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exit(1);
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}
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}
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else if (!strcmp(argv[i], "--arraysize") || !strcmp(argv[i], "-s"))
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{
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if (++i >= argc || !parseUInt(argv[i], &ARRAY_SIZE))
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{
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std::cout << "Invalid array size" << std::endl;
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exit(1);
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}
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}
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else if (!strcmp(argv[i], "--numtimes") || !strcmp(argv[i], "-n"))
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{
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if (++i >= argc || !parseUInt(argv[i], &NTIMES))
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{
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std::cout << "Invalid number of times" << std::endl;
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exit(1);
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}
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}
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else if (!strcmp(argv[i], "--float"))
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{
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useFloat = true;
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DATATYPE_SIZE = sizeof(float);
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}
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else if (!strcmp(argv[i], "--help") || !strcmp(argv[i], "-h"))
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{
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std::cout << std::endl;
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std::cout << "Usage: ./gpu-stream-cuda [OPTIONS]" << std::endl << std::endl;
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std::cout << "Options:" << std::endl;
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std::cout << " -h --help Print the message" << std::endl;
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std::cout << " --list List available devices" << std::endl;
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std::cout << " --device INDEX Select device at INDEX" << std::endl;
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std::cout << " -s --arraysize SIZE Use SIZE elements in the array" << std::endl;
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std::cout << " -n --numtimes NUM Run the test NUM times (NUM >= 2)" << std::endl;
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std::cout << " --float Use floats (rather than doubles)" << std::endl;
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std::cout << std::endl;
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exit(0);
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}
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else
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{
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std::cout << "Unrecognized argument '" << argv[i] << "' (try '--help')"
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<< std::endl;
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exit(1);
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}
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}
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}
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