mirror of
https://github.com/NVIDIA/cuda-samples.git
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244 lines
9.1 KiB
Plaintext
244 lines
9.1 KiB
Plaintext
/* Copyright (c) 2022, 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 and put prices for a
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* given set of European options by Black-Scholes formula.
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* See supplied whitepaper for more explanations.
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*/
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#include <helper_functions.h> // helper functions for string parsing
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#include <helper_cuda.h> // helper functions CUDA error checking and initialization
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////////////////////////////////////////////////////////////////////////////////
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// Process an array of optN options on CPU
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////////////////////////////////////////////////////////////////////////////////
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extern "C" void BlackScholesCPU(float *h_CallResult, float *h_PutResult,
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float *h_StockPrice, float *h_OptionStrike,
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float *h_OptionYears, float Riskfree,
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float Volatility, int optN);
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////////////////////////////////////////////////////////////////////////////////
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// Process an array of OptN options on GPU
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////////////////////////////////////////////////////////////////////////////////
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#include "BlackScholes_kernel.cuh"
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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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float RandFloat(float low, float high) {
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float t = (float)rand() / (float)RAND_MAX;
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return (1.0f - t) * low + t * high;
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}
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////////////////////////////////////////////////////////////////////////////////
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// Data configuration
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////////////////////////////////////////////////////////////////////////////////
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const int OPT_N = 4000000;
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const int NUM_ITERATIONS = 512;
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const int OPT_SZ = OPT_N * sizeof(float);
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const float RISKFREE = 0.02f;
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const float VOLATILITY = 0.30f;
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#define DIV_UP(a, b) (((a) + (b)-1) / (b))
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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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// Start logs
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printf("[%s] - Starting...\n", argv[0]);
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//'h_' prefix - CPU (host) memory space
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float
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// Results calculated by CPU for reference
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*h_CallResultCPU,
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*h_PutResultCPU,
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// CPU copy of GPU results
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*h_CallResultGPU, *h_PutResultGPU,
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// CPU instance of input data
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*h_StockPrice, *h_OptionStrike, *h_OptionYears;
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//'d_' prefix - GPU (device) memory space
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float
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// Results calculated by GPU
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*d_CallResult,
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*d_PutResult,
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// GPU instance of input data
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*d_StockPrice, *d_OptionStrike, *d_OptionYears;
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double delta, ref, sum_delta, sum_ref, max_delta, L1norm, gpuTime;
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StopWatchInterface *hTimer = NULL;
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int i;
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findCudaDevice(argc, (const char **)argv);
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sdkCreateTimer(&hTimer);
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printf("Initializing data...\n");
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printf("...allocating CPU memory for options.\n");
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h_CallResultCPU = (float *)malloc(OPT_SZ);
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h_PutResultCPU = (float *)malloc(OPT_SZ);
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h_CallResultGPU = (float *)malloc(OPT_SZ);
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h_PutResultGPU = (float *)malloc(OPT_SZ);
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h_StockPrice = (float *)malloc(OPT_SZ);
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h_OptionStrike = (float *)malloc(OPT_SZ);
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h_OptionYears = (float *)malloc(OPT_SZ);
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printf("...allocating GPU memory for options.\n");
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checkCudaErrors(cudaMalloc((void **)&d_CallResult, OPT_SZ));
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checkCudaErrors(cudaMalloc((void **)&d_PutResult, OPT_SZ));
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checkCudaErrors(cudaMalloc((void **)&d_StockPrice, OPT_SZ));
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checkCudaErrors(cudaMalloc((void **)&d_OptionStrike, OPT_SZ));
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checkCudaErrors(cudaMalloc((void **)&d_OptionYears, OPT_SZ));
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printf("...generating input data in CPU mem.\n");
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srand(5347);
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// Generate options set
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for (i = 0; i < OPT_N; i++) {
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h_CallResultCPU[i] = 0.0f;
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h_PutResultCPU[i] = -1.0f;
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h_StockPrice[i] = RandFloat(5.0f, 30.0f);
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h_OptionStrike[i] = RandFloat(1.0f, 100.0f);
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h_OptionYears[i] = RandFloat(0.25f, 10.0f);
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}
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printf("...copying input data to GPU mem.\n");
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// Copy options data to GPU memory for further processing
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checkCudaErrors(
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cudaMemcpy(d_StockPrice, h_StockPrice, OPT_SZ, cudaMemcpyHostToDevice));
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checkCudaErrors(cudaMemcpy(d_OptionStrike, h_OptionStrike, OPT_SZ,
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cudaMemcpyHostToDevice));
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checkCudaErrors(
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cudaMemcpy(d_OptionYears, h_OptionYears, OPT_SZ, cudaMemcpyHostToDevice));
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printf("Data init done.\n\n");
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printf("Executing Black-Scholes GPU kernel (%i iterations)...\n",
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NUM_ITERATIONS);
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checkCudaErrors(cudaDeviceSynchronize());
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sdkResetTimer(&hTimer);
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sdkStartTimer(&hTimer);
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for (i = 0; i < NUM_ITERATIONS; i++) {
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BlackScholesGPU<<<DIV_UP((OPT_N / 2), 128), 128 /*480, 128*/>>>(
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(float2 *)d_CallResult, (float2 *)d_PutResult, (float2 *)d_StockPrice,
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(float2 *)d_OptionStrike, (float2 *)d_OptionYears, RISKFREE, VOLATILITY,
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OPT_N);
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getLastCudaError("BlackScholesGPU() execution failed\n");
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}
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checkCudaErrors(cudaDeviceSynchronize());
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sdkStopTimer(&hTimer);
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gpuTime = sdkGetTimerValue(&hTimer) / NUM_ITERATIONS;
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// Both call and put is calculated
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printf("Options count : %i \n", 2 * OPT_N);
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printf("BlackScholesGPU() time : %f msec\n", gpuTime);
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printf("Effective memory bandwidth: %f GB/s\n",
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((double)(5 * OPT_N * sizeof(float)) * 1E-9) / (gpuTime * 1E-3));
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printf("Gigaoptions per second : %f \n\n",
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((double)(2 * OPT_N) * 1E-9) / (gpuTime * 1E-3));
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printf(
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"BlackScholes, Throughput = %.4f GOptions/s, Time = %.5f s, Size = %u "
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"options, NumDevsUsed = %u, Workgroup = %u\n",
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(((double)(2.0 * OPT_N) * 1.0E-9) / (gpuTime * 1.0E-3)), gpuTime * 1e-3,
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(2 * OPT_N), 1, 128);
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printf("\nReading back GPU results...\n");
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// Read back GPU results to compare them to CPU results
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checkCudaErrors(cudaMemcpy(h_CallResultGPU, d_CallResult, OPT_SZ,
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cudaMemcpyDeviceToHost));
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checkCudaErrors(
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cudaMemcpy(h_PutResultGPU, d_PutResult, OPT_SZ, cudaMemcpyDeviceToHost));
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printf("Checking the results...\n");
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printf("...running CPU calculations.\n\n");
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// Calculate options values on CPU
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BlackScholesCPU(h_CallResultCPU, h_PutResultCPU, h_StockPrice, h_OptionStrike,
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h_OptionYears, RISKFREE, VOLATILITY, OPT_N);
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printf("Comparing the results...\n");
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// Calculate max absolute difference and L1 distance
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// between CPU and GPU results
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sum_delta = 0;
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sum_ref = 0;
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max_delta = 0;
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for (i = 0; i < OPT_N; i++) {
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ref = h_CallResultCPU[i];
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delta = fabs(h_CallResultCPU[i] - h_CallResultGPU[i]);
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if (delta > max_delta) {
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max_delta = delta;
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}
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sum_delta += delta;
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sum_ref += fabs(ref);
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}
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L1norm = sum_delta / sum_ref;
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printf("L1 norm: %E\n", L1norm);
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printf("Max absolute error: %E\n\n", max_delta);
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printf("Shutting down...\n");
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printf("...releasing GPU memory.\n");
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checkCudaErrors(cudaFree(d_OptionYears));
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checkCudaErrors(cudaFree(d_OptionStrike));
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checkCudaErrors(cudaFree(d_StockPrice));
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checkCudaErrors(cudaFree(d_PutResult));
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checkCudaErrors(cudaFree(d_CallResult));
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printf("...releasing CPU memory.\n");
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free(h_OptionYears);
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free(h_OptionStrike);
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free(h_StockPrice);
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free(h_PutResultGPU);
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free(h_CallResultGPU);
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free(h_PutResultCPU);
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free(h_CallResultCPU);
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sdkDeleteTimer(&hTimer);
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printf("Shutdown done.\n");
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printf("\n[BlackScholes] - Test Summary\n");
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if (L1norm > 1e-6) {
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printf("Test failed!\n");
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exit(EXIT_FAILURE);
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}
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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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printf("Test passed\n");
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exit(EXIT_SUCCESS);
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}
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