2022-01-13 14:05:24 +08:00
|
|
|
/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
|
2021-10-21 19:04:49 +08:00
|
|
|
*
|
|
|
|
* 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.
|
|
|
|
*/
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
// Global types and parameters
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
|
|
|
|
#include <stdio.h>
|
|
|
|
#include <stdlib.h>
|
|
|
|
#include <cmath>
|
|
|
|
|
|
|
|
#include <helper_cuda.h>
|
|
|
|
#include <nvrtc_helper.h>
|
|
|
|
#include <cuda_runtime.h>
|
|
|
|
|
|
|
|
#include "binomialOptions_common.h"
|
|
|
|
|
|
|
|
#include "common_gpu_header.h"
|
|
|
|
#include "realtype.h"
|
|
|
|
|
|
|
|
// Preprocessed input option data
|
|
|
|
typedef struct {
|
|
|
|
real S;
|
|
|
|
real X;
|
|
|
|
real vDt;
|
|
|
|
real puByDf;
|
|
|
|
real pdByDf;
|
|
|
|
|
|
|
|
} __TOptionData;
|
|
|
|
|
|
|
|
static bool moduleLoaded = false;
|
|
|
|
char *cubin, *kernel_file;
|
|
|
|
size_t cubinSize;
|
|
|
|
CUmodule module;
|
|
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
// Host-side interface to GPU binomialOptions
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
|
|
|
|
extern "C" void binomialOptionsGPU(real *callValue, TOptionData *optionData,
|
|
|
|
int optN, int argc, char **argv) {
|
|
|
|
if (!moduleLoaded) {
|
|
|
|
kernel_file = sdkFindFilePath("binomialOptions_kernel.cu", argv[0]);
|
|
|
|
compileFileToCUBIN(kernel_file, argc, argv, &cubin, &cubinSize, 0);
|
|
|
|
module = loadCUBIN(cubin, argc, argv);
|
|
|
|
moduleLoaded = true;
|
|
|
|
}
|
|
|
|
|
|
|
|
__TOptionData h_OptionData[MAX_OPTIONS];
|
|
|
|
|
|
|
|
for (int i = 0; i < optN; i++) {
|
|
|
|
const real T = optionData[i].T;
|
|
|
|
const real R = optionData[i].R;
|
|
|
|
const real V = optionData[i].V;
|
|
|
|
|
|
|
|
const real dt = T / (real)NUM_STEPS;
|
|
|
|
const real vDt = V * sqrt(dt);
|
|
|
|
const real rDt = R * dt;
|
|
|
|
// Per-step interest and discount factors
|
|
|
|
const real If = exp(rDt);
|
|
|
|
const real Df = exp(-rDt);
|
|
|
|
// Values and pseudoprobabilities of upward and downward moves
|
|
|
|
const real u = exp(vDt);
|
|
|
|
const real d = exp(-vDt);
|
|
|
|
const real pu = (If - d) / (u - d);
|
|
|
|
const real pd = (real)1.0 - pu;
|
|
|
|
const real puByDf = pu * Df;
|
|
|
|
const real pdByDf = pd * Df;
|
|
|
|
|
|
|
|
h_OptionData[i].S = (real)optionData[i].S;
|
|
|
|
h_OptionData[i].X = (real)optionData[i].X;
|
|
|
|
h_OptionData[i].vDt = (real)vDt;
|
|
|
|
h_OptionData[i].puByDf = (real)puByDf;
|
|
|
|
h_OptionData[i].pdByDf = (real)pdByDf;
|
|
|
|
}
|
|
|
|
|
|
|
|
CUfunction kernel_addr;
|
|
|
|
checkCudaErrors(
|
|
|
|
cuModuleGetFunction(&kernel_addr, module, "binomialOptionsKernel"));
|
|
|
|
|
|
|
|
CUdeviceptr d_OptionData;
|
|
|
|
checkCudaErrors(
|
|
|
|
cuModuleGetGlobal(&d_OptionData, NULL, module, "d_OptionData"));
|
|
|
|
checkCudaErrors(
|
|
|
|
cuMemcpyHtoD(d_OptionData, h_OptionData, optN * sizeof(__TOptionData)));
|
|
|
|
|
|
|
|
dim3 cudaBlockSize(128, 1, 1);
|
|
|
|
dim3 cudaGridSize(optN, 1, 1);
|
|
|
|
|
|
|
|
checkCudaErrors(cuLaunchKernel(kernel_addr, cudaGridSize.x, cudaGridSize.y,
|
|
|
|
cudaGridSize.z, /* grid dim */
|
|
|
|
cudaBlockSize.x, cudaBlockSize.y,
|
|
|
|
cudaBlockSize.z, /* block dim */
|
|
|
|
0, 0, /* shared mem, stream */
|
|
|
|
NULL, /* arguments */
|
|
|
|
0));
|
|
|
|
|
|
|
|
checkCudaErrors(cuCtxSynchronize());
|
|
|
|
|
|
|
|
CUdeviceptr d_CallValue;
|
|
|
|
checkCudaErrors(cuModuleGetGlobal(&d_CallValue, NULL, module, "d_CallValue"));
|
|
|
|
checkCudaErrors(cuMemcpyDtoH(callValue, d_CallValue, optN * sizeof(real)));
|
|
|
|
}
|