mirror of
https://github.com/NVIDIA/cuda-samples.git
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189 lines
6.3 KiB
C++
189 lines
6.3 KiB
C++
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/* Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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* * Neither the name of NVIDIA CORPORATION nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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/*
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* This sample evaluates fair call price for a
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* given set of European options under binomial model.
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* See supplied whitepaper for more explanations.
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*/
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#include <stdlib.h>
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#include <stdio.h>
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#include <string.h>
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#include <math.h>
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#include <cuda_runtime.h>
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#include <helper_functions.h>
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#include <helper_cuda.h>
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#include "binomialOptions_common.h"
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#include "realtype.h"
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////////////////////////////////////////////////////////////////////////////////
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// Black-Scholes formula for binomial tree results validation
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////////////////////////////////////////////////////////////////////////////////
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extern "C" void BlackScholesCall(real &callResult, TOptionData optionData);
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////////////////////////////////////////////////////////////////////////////////
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// Process single option on CPU
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// Note that CPU code is for correctness testing only and not for benchmarking.
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////////////////////////////////////////////////////////////////////////////////
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extern "C" void binomialOptionsCPU(real &callResult, TOptionData optionData);
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////////////////////////////////////////////////////////////////////////////////
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// Process an array of OptN options on GPU
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////////////////////////////////////////////////////////////////////////////////
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extern "C" void binomialOptionsGPU(real *callValue, TOptionData *optionData,
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int optN);
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////////////////////////////////////////////////////////////////////////////////
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// Helper function, returning uniformly distributed
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// random float in [low, high] range
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////////////////////////////////////////////////////////////////////////////////
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real randData(real low, real high) {
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real t = (real)rand() / (real)RAND_MAX;
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return ((real)1.0 - t) * low + t * high;
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}
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////////////////////////////////////////////////////////////////////////////////
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// Main program
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////////////////////////////////////////////////////////////////////////////////
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int main(int argc, char **argv) {
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printf("[%s] - Starting...\n", argv[0]);
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int devID = findCudaDevice(argc, (const char **)argv);
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const int OPT_N = MAX_OPTIONS;
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TOptionData optionData[MAX_OPTIONS];
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real callValueBS[MAX_OPTIONS], callValueGPU[MAX_OPTIONS],
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callValueCPU[MAX_OPTIONS];
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real sumDelta, sumRef, gpuTime, errorVal;
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StopWatchInterface *hTimer = NULL;
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int i;
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sdkCreateTimer(&hTimer);
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printf("Generating input data...\n");
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// Generate options set
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srand(123);
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for (i = 0; i < OPT_N; i++) {
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optionData[i].S = randData(5.0f, 30.0f);
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optionData[i].X = randData(1.0f, 100.0f);
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optionData[i].T = randData(0.25f, 10.0f);
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optionData[i].R = 0.06f;
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optionData[i].V = 0.10f;
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BlackScholesCall(callValueBS[i], optionData[i]);
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}
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printf("Running GPU binomial tree...\n");
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checkCudaErrors(cudaDeviceSynchronize());
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sdkResetTimer(&hTimer);
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sdkStartTimer(&hTimer);
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binomialOptionsGPU(callValueGPU, optionData, OPT_N);
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checkCudaErrors(cudaDeviceSynchronize());
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sdkStopTimer(&hTimer);
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gpuTime = sdkGetTimerValue(&hTimer);
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printf("Options count : %i \n", OPT_N);
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printf("Time steps : %i \n", NUM_STEPS);
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printf("binomialOptionsGPU() time: %f msec\n", gpuTime);
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printf("Options per second : %f \n", OPT_N / (gpuTime * 0.001));
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printf("Running CPU binomial tree...\n");
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for (i = 0; i < OPT_N; i++) {
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binomialOptionsCPU(callValueCPU[i], optionData[i]);
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}
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printf("Comparing the results...\n");
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sumDelta = 0;
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sumRef = 0;
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printf("GPU binomial vs. Black-Scholes\n");
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for (i = 0; i < OPT_N; i++) {
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sumDelta += fabs(callValueBS[i] - callValueGPU[i]);
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sumRef += fabs(callValueBS[i]);
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}
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if (sumRef > 1E-5) {
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printf("L1 norm: %E\n", (double)(sumDelta / sumRef));
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} else {
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printf("Avg. diff: %E\n", (double)(sumDelta / (real)OPT_N));
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}
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printf("CPU binomial vs. Black-Scholes\n");
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sumDelta = 0;
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sumRef = 0;
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for (i = 0; i < OPT_N; i++) {
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sumDelta += fabs(callValueBS[i] - callValueCPU[i]);
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sumRef += fabs(callValueBS[i]);
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}
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if (sumRef > 1E-5) {
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printf("L1 norm: %E\n", sumDelta / sumRef);
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} else {
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printf("Avg. diff: %E\n", (double)(sumDelta / (real)OPT_N));
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}
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printf("CPU binomial vs. GPU binomial\n");
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sumDelta = 0;
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sumRef = 0;
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for (i = 0; i < OPT_N; i++) {
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sumDelta += fabs(callValueGPU[i] - callValueCPU[i]);
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sumRef += callValueCPU[i];
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}
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if (sumRef > 1E-5) {
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printf("L1 norm: %E\n", errorVal = sumDelta / sumRef);
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} else {
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printf("Avg. diff: %E\n", (double)(sumDelta / (real)OPT_N));
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}
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printf("Shutting down...\n");
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sdkDeleteTimer(&hTimer);
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printf(
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"\nNOTE: The CUDA Samples are not meant for performance measurements. "
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"Results may vary when GPU Boost is enabled.\n\n");
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if (errorVal > 5e-4) {
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printf("Test failed!\n");
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exit(EXIT_FAILURE);
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}
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printf("Test passed\n");
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exit(EXIT_SUCCESS);
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}
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