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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/*
* This sample evaluates fair call price for a
* given set of European options under binomial model.
* See supplied whitepaper for more explanations.
*/
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>
#include <cuda_runtime.h>
#include <helper_functions.h>
#include <helper_cuda.h>
#include "binomialOptions_common.h"
#include "realtype.h"
////////////////////////////////////////////////////////////////////////////////
// Black-Scholes formula for binomial tree results validation
////////////////////////////////////////////////////////////////////////////////
extern "C" void BlackScholesCall(real &callResult, TOptionData optionData);
////////////////////////////////////////////////////////////////////////////////
// Process single option on CPU
// Note that CPU code is for correctness testing only and not for benchmarking.
////////////////////////////////////////////////////////////////////////////////
extern "C" void binomialOptionsCPU(real &callResult, TOptionData optionData);
////////////////////////////////////////////////////////////////////////////////
// Process an array of OptN options on GPU
////////////////////////////////////////////////////////////////////////////////
extern "C" void binomialOptionsGPU(real *callValue, TOptionData *optionData,
int optN);
////////////////////////////////////////////////////////////////////////////////
// Helper function, returning uniformly distributed
// random float in [low, high] range
////////////////////////////////////////////////////////////////////////////////
real randData(real low, real high) {
real t = (real)rand() / (real)RAND_MAX;
return ((real)1.0 - t) * low + t * high;
}
////////////////////////////////////////////////////////////////////////////////
// Main program
////////////////////////////////////////////////////////////////////////////////
int main(int argc, char **argv) {
printf("[%s] - Starting...\n", argv[0]);
int devID = findCudaDevice(argc, (const char **)argv);
const int OPT_N = MAX_OPTIONS;
TOptionData optionData[MAX_OPTIONS];
real callValueBS[MAX_OPTIONS], callValueGPU[MAX_OPTIONS],
callValueCPU[MAX_OPTIONS];
real sumDelta, sumRef, gpuTime, errorVal;
StopWatchInterface *hTimer = NULL;
int i;
sdkCreateTimer(&hTimer);
printf("Generating input data...\n");
// Generate options set
srand(123);
for (i = 0; i < OPT_N; i++) {
optionData[i].S = randData(5.0f, 30.0f);
optionData[i].X = randData(1.0f, 100.0f);
optionData[i].T = randData(0.25f, 10.0f);
optionData[i].R = 0.06f;
optionData[i].V = 0.10f;
BlackScholesCall(callValueBS[i], optionData[i]);
}
printf("Running GPU binomial tree...\n");
checkCudaErrors(cudaDeviceSynchronize());
sdkResetTimer(&hTimer);
sdkStartTimer(&hTimer);
binomialOptionsGPU(callValueGPU, optionData, OPT_N);
checkCudaErrors(cudaDeviceSynchronize());
sdkStopTimer(&hTimer);
gpuTime = sdkGetTimerValue(&hTimer);
printf("Options count : %i \n", OPT_N);
printf("Time steps : %i \n", NUM_STEPS);
printf("binomialOptionsGPU() time: %f msec\n", gpuTime);
printf("Options per second : %f \n", OPT_N / (gpuTime * 0.001));
printf("Running CPU binomial tree...\n");
for (i = 0; i < OPT_N; i++) {
binomialOptionsCPU(callValueCPU[i], optionData[i]);
}
printf("Comparing the results...\n");
sumDelta = 0;
sumRef = 0;
printf("GPU binomial vs. Black-Scholes\n");
for (i = 0; i < OPT_N; i++) {
sumDelta += fabs(callValueBS[i] - callValueGPU[i]);
sumRef += fabs(callValueBS[i]);
}
if (sumRef > 1E-5) {
printf("L1 norm: %E\n", (double)(sumDelta / sumRef));
} else {
printf("Avg. diff: %E\n", (double)(sumDelta / (real)OPT_N));
}
printf("CPU binomial vs. Black-Scholes\n");
sumDelta = 0;
sumRef = 0;
for (i = 0; i < OPT_N; i++) {
sumDelta += fabs(callValueBS[i] - callValueCPU[i]);
sumRef += fabs(callValueBS[i]);
}
if (sumRef > 1E-5) {
printf("L1 norm: %E\n", sumDelta / sumRef);
} else {
printf("Avg. diff: %E\n", (double)(sumDelta / (real)OPT_N));
}
printf("CPU binomial vs. GPU binomial\n");
sumDelta = 0;
sumRef = 0;
for (i = 0; i < OPT_N; i++) {
sumDelta += fabs(callValueGPU[i] - callValueCPU[i]);
sumRef += callValueCPU[i];
}
if (sumRef > 1E-5) {
printf("L1 norm: %E\n", errorVal = sumDelta / sumRef);
} else {
printf("Avg. diff: %E\n", (double)(sumDelta / (real)OPT_N));
}
printf("Shutting down...\n");
sdkDeleteTimer(&hTimer);
printf(
"\nNOTE: The CUDA Samples are not meant for performance measurements. "
"Results may vary when GPU Boost is enabled.\n\n");
if (errorVal > 5e-4) {
printf("Test failed!\n");
exit(EXIT_FAILURE);
}
printf("Test passed\n");
exit(EXIT_SUCCESS);
}
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