cuda-samples/Samples/binomialOptions_nvrtc/binomialOptions_kernel.cu
2021-10-21 16:34:49 +05:30

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/* Copyright (c) 2021, 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
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* 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
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#include "common_gpu_header.h"
#include "binomialOptions_common.h"
#include "realtype.h"
// Preprocessed input option data
typedef struct {
real S;
real X;
real vDt;
real puByDf;
real pdByDf;
} __TOptionData;
static __constant__ __TOptionData d_OptionData[MAX_OPTIONS];
__device__ real d_CallValue[MAX_OPTIONS];
#define THREADBLOCK_SIZE 128
#define ELEMS_PER_THREAD (NUM_STEPS / THREADBLOCK_SIZE)
#if NUM_STEPS % THREADBLOCK_SIZE
#error Bad constants
#endif
////////////////////////////////////////////////////////////////////////////////
// Overloaded shortcut functions for different precision modes
////////////////////////////////////////////////////////////////////////////////
#ifndef DOUBLE_PRECISION
__device__ inline float expiryCallValue(float S, float X, float vDt, int i) {
float d = S * __expf(vDt * (2.0f * i - NUM_STEPS)) - X;
return (d > 0.0F) ? d : 0.0F;
}
#else
__device__ inline double expiryCallValue(double S, double X, double vDt,
int i) {
double d = S * exp(vDt * (2.0 * i - NUM_STEPS)) - X;
return (d > 0.0) ? d : 0.0;
}
#endif
////////////////////////////////////////////////////////////////////////////////
// GPU kernel
////////////////////////////////////////////////////////////////////////////////
extern "C" __global__ void binomialOptionsKernel() {
__shared__ real call_exchange[THREADBLOCK_SIZE + 1];
const int tid = threadIdx.x;
const real S = d_OptionData[blockIdx.x].S;
const real X = d_OptionData[blockIdx.x].X;
const real vDt = d_OptionData[blockIdx.x].vDt;
const real puByDf = d_OptionData[blockIdx.x].puByDf;
const real pdByDf = d_OptionData[blockIdx.x].pdByDf;
real call[ELEMS_PER_THREAD + 1];
#pragma unroll
for (int i = 0; i < ELEMS_PER_THREAD; ++i)
call[i] = expiryCallValue(S, X, vDt, tid * ELEMS_PER_THREAD + i);
if (tid == 0)
call_exchange[THREADBLOCK_SIZE] = expiryCallValue(S, X, vDt, NUM_STEPS);
int final_it = max(0, tid * ELEMS_PER_THREAD - 1);
#pragma unroll 16
for (int i = NUM_STEPS; i > 0; --i) {
call_exchange[tid] = call[0];
__syncthreads();
call[ELEMS_PER_THREAD] = call_exchange[tid + 1];
__syncthreads();
if (i > final_it) {
#pragma unroll
for (int j = 0; j < ELEMS_PER_THREAD; ++j)
call[j] = puByDf * call[j + 1] + pdByDf * call[j];
}
}
if (tid == 0) {
d_CallValue[blockIdx.x] = call[0];
}
}