mirror of
https://github.com/NVIDIA/cuda-samples.git
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128 lines
4.7 KiB
C++
128 lines
4.7 KiB
C++
/* 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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// Global types and parameters
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////////////////////////////////////////////////////////////////////////////////
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#include <stdio.h>
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#include <stdlib.h>
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#include <cmath>
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#include <helper_cuda.h>
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#include <nvrtc_helper.h>
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#include <cuda_runtime.h>
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#include "binomialOptions_common.h"
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#include "common_gpu_header.h"
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#include "realtype.h"
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// Preprocessed input option data
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typedef struct {
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real S;
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real X;
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real vDt;
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real puByDf;
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real pdByDf;
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} __TOptionData;
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static bool moduleLoaded = false;
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char *cubin, *kernel_file;
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size_t cubinSize;
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CUmodule module;
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////////////////////////////////////////////////////////////////////////////////
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// Host-side interface to GPU binomialOptions
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////////////////////////////////////////////////////////////////////////////////
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extern "C" void binomialOptionsGPU(real *callValue, TOptionData *optionData,
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int optN, int argc, char **argv) {
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if (!moduleLoaded) {
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kernel_file = sdkFindFilePath("binomialOptions_kernel.cu", argv[0]);
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compileFileToCUBIN(kernel_file, argc, argv, &cubin, &cubinSize, 0);
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module = loadCUBIN(cubin, argc, argv);
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moduleLoaded = true;
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}
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__TOptionData h_OptionData[MAX_OPTIONS];
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for (int i = 0; i < optN; i++) {
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const real T = optionData[i].T;
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const real R = optionData[i].R;
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const real V = optionData[i].V;
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const real dt = T / (real)NUM_STEPS;
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const real vDt = V * sqrt(dt);
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const real rDt = R * dt;
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// Per-step interest and discount factors
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const real If = exp(rDt);
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const real Df = exp(-rDt);
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// Values and pseudoprobabilities of upward and downward moves
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const real u = exp(vDt);
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const real d = exp(-vDt);
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const real pu = (If - d) / (u - d);
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const real pd = (real)1.0 - pu;
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const real puByDf = pu * Df;
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const real pdByDf = pd * Df;
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h_OptionData[i].S = (real)optionData[i].S;
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h_OptionData[i].X = (real)optionData[i].X;
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h_OptionData[i].vDt = (real)vDt;
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h_OptionData[i].puByDf = (real)puByDf;
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h_OptionData[i].pdByDf = (real)pdByDf;
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}
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CUfunction kernel_addr;
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checkCudaErrors(
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cuModuleGetFunction(&kernel_addr, module, "binomialOptionsKernel"));
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CUdeviceptr d_OptionData;
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checkCudaErrors(
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cuModuleGetGlobal(&d_OptionData, NULL, module, "d_OptionData"));
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checkCudaErrors(
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cuMemcpyHtoD(d_OptionData, h_OptionData, optN * sizeof(__TOptionData)));
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dim3 cudaBlockSize(128, 1, 1);
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dim3 cudaGridSize(optN, 1, 1);
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checkCudaErrors(cuLaunchKernel(kernel_addr, cudaGridSize.x, cudaGridSize.y,
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cudaGridSize.z, /* grid dim */
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cudaBlockSize.x, cudaBlockSize.y,
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cudaBlockSize.z, /* block dim */
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0, 0, /* shared mem, stream */
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NULL, /* arguments */
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0));
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checkCudaErrors(cuCtxSynchronize());
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CUdeviceptr d_CallValue;
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checkCudaErrors(cuModuleGetGlobal(&d_CallValue, NULL, module, "d_CallValue"));
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checkCudaErrors(cuMemcpyDtoH(callValue, d_CallValue, optN * sizeof(real)));
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}
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