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added cuda examples

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Evghenii
2013-11-04 11:44:49 +01:00
parent cb6614da42
commit cb7cbec0d5
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1
examples_cuda/options/.gitignore vendored Normal file
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options

8
examples_cuda/options/Makefile Normal file
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EXAMPLE=options
CPP_SRC=options.cpp options_serial.cpp
ISPC_SRC=options.ispc
ISPC_IA_TARGETS=sse2,sse4-x2,avx-x2
ISPC_ARM_TARGETS=neon
include ../common.mk

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examples_cuda/options/options.cpp Normal file
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/*
Copyright (c) 2010-2011, Intel 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 Intel 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 AND CONTRIBUTORS "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.
*/
#define NOMINMAX
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <assert.h>
#include <math.h>
#include <algorithm>
using std::max;
#include "options_defs.h"
#include "../timing.h"
#include "options_ispc.h"
using namespace ispc;
extern void black_scholes_serial(float Sa[], float Xa[], float Ta[],
float ra[], float va[],
float result[], int count);
extern void binomial_put_serial(float Sa[], float Xa[], float Ta[],
float ra[], float va[],
float result[], int count);
static void usage() {
printf("usage: options [--count=<num options>]\n");
}
int main(int argc, char *argv[]) {
int nOptions = 128*1024;
for (int i = 1; i < argc; ++i) {
if (strncmp(argv[i], "--count=", 8) == 0) {
nOptions = atoi(argv[i] + 8);
if (nOptions <= 0) {
usage();
exit(1);
}
}
}
float *S = new float[nOptions];
float *X = new float[nOptions];
float *T = new float[nOptions];
float *r = new float[nOptions];
float *v = new float[nOptions];
float *result = new float[nOptions];
for (int i = 0; i < nOptions; ++i) {
S[i] = 100; // stock price
X[i] = 98; // option strike price
T[i] = 2; // time (years)
r[i] = .02; // risk-free interest rate
v[i] = 5; // volatility
}
double sum;
//
// Binomial options pricing model, ispc implementation
//
double binomial_ispc = 1e30;
for (int i = 0; i < 3; ++i) {
reset_and_start_timer();
binomial_put_ispc(S, X, T, r, v, result, nOptions);
double dt = get_elapsed_mcycles();
sum = 0.;
for (int i = 0; i < nOptions; ++i)
sum += result[i];
binomial_ispc = std::min(binomial_ispc, dt);
}
printf("[binomial ispc, 1 thread]:\t[%.3f] million cycles (avg %f)\n",
binomial_ispc, sum / nOptions);
//
// Binomial options pricing model, ispc implementation, tasks
//
double binomial_tasks = 1e30;
for (int i = 0; i < 3; ++i) {
reset_and_start_timer();
binomial_put_ispc_tasks(S, X, T, r, v, result, nOptions);
double dt = get_elapsed_mcycles();
sum = 0.;
for (int i = 0; i < nOptions; ++i)
sum += result[i];
binomial_tasks = std::min(binomial_tasks, dt);
}
printf("[binomial ispc, tasks]:\t\t[%.3f] million cycles (avg %f)\n",
binomial_tasks, sum / nOptions);
//
// Binomial options, serial implementation
//
double binomial_serial = 1e30;
for (int i = 0; i < 3; ++i) {
reset_and_start_timer();
binomial_put_serial(S, X, T, r, v, result, nOptions);
double dt = get_elapsed_mcycles();
sum = 0.;
for (int i = 0; i < nOptions; ++i)
sum += result[i];
binomial_serial = std::min(binomial_serial, dt);
}
printf("[binomial serial]:\t\t[%.3f] million cycles (avg %f)\n",
binomial_serial, sum / nOptions);
printf("\t\t\t\t(%.2fx speedup from ISPC, %.2fx speedup from ISPC + tasks)\n",
binomial_serial / binomial_ispc, binomial_serial / binomial_tasks);
//
// Black-Scholes options pricing model, ispc implementation, 1 thread
//
double bs_ispc = 1e30;
for (int i = 0; i < 3; ++i) {
reset_and_start_timer();
black_scholes_ispc(S, X, T, r, v, result, nOptions);
double dt = get_elapsed_mcycles();
sum = 0.;
for (int i = 0; i < nOptions; ++i)
sum += result[i];
bs_ispc = std::min(bs_ispc, dt);
}
printf("[black-scholes ispc, 1 thread]:\t[%.3f] million cycles (avg %f)\n",
bs_ispc, sum / nOptions);
//
// Black-Scholes options pricing model, ispc implementation, tasks
//
double bs_ispc_tasks = 1e30;
for (int i = 0; i < 3; ++i) {
reset_and_start_timer();
black_scholes_ispc_tasks(S, X, T, r, v, result, nOptions);
double dt = get_elapsed_mcycles();
sum = 0.;
for (int i = 0; i < nOptions; ++i)
sum += result[i];
bs_ispc_tasks = std::min(bs_ispc_tasks, dt);
}
printf("[black-scholes ispc, tasks]:\t[%.3f] million cycles (avg %f)\n",
bs_ispc_tasks, sum / nOptions);
//
// Black-Scholes options pricing model, serial implementation
//
double bs_serial = 1e30;
for (int i = 0; i < 3; ++i) {
reset_and_start_timer();
black_scholes_serial(S, X, T, r, v, result, nOptions);
double dt = get_elapsed_mcycles();
sum = 0.;
for (int i = 0; i < nOptions; ++i)
sum += result[i];
bs_serial = std::min(bs_serial, dt);
}
printf("[black-scholes serial]:\t\t[%.3f] million cycles (avg %f)\n", bs_serial,
sum / nOptions);
printf("\t\t\t\t(%.2fx speedup from ISPC, %.2fx speedup from ISPC + tasks)\n",
bs_serial / bs_ispc, bs_serial / bs_ispc_tasks);
return 0;
}

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examples_cuda/options/options.ispc Normal file
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// -*- mode: c++ -*-
/*
Copyright (c) 2010-2011, Intel 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 Intel 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 AND CONTRIBUTORS "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.
*/
#include "options_defs.h"
// Cumulative normal distribution function
static inline float
CND(float X) {
float L = abs(X);
float k = 1.0 / (1.0 + 0.2316419 * L);
float k2 = k*k;
float k3 = k2*k;
float k4 = k2*k2;
float k5 = k3*k2;
const float invSqrt2Pi = 0.39894228040f;
float w = (0.31938153f * k - 0.356563782f * k2 + 1.781477937f * k3 +
-1.821255978f * k4 + 1.330274429f * k5);
w *= invSqrt2Pi * exp(-L * L * .5f);
if (X > 0.f)
w = 1.0 - w;
return w;
}
task void
bs_task(uniform float Sa[], uniform float Xa[], uniform float Ta[],
uniform float ra[], uniform float va[],
uniform float result[], uniform int count) {
uniform int first = taskIndex * (count/taskCount);
uniform int last = min(count, (int)((taskIndex+1) * (count/taskCount)));
foreach (i = first ... last) {
float S = Sa[i], X = Xa[i], T = Ta[i], r = ra[i], v = va[i];
float d1 = (log(S/X) + (r + v * v * .5f) * T) / (v * sqrt(T));
float d2 = d1 - v * sqrt(T);
result[i] = S * CND(d1) - X * exp(-r * T) * CND(d2);
}
}
export void
black_scholes_ispc_tasks(uniform float Sa[], uniform float Xa[], uniform float Ta[],
uniform float ra[], uniform float va[],
uniform float result[], uniform int count) {
uniform int nTasks = max((int)64, (int)count/16384);
launch[nTasks] bs_task(Sa, Xa, Ta, ra, va, result, count);
}
export void
black_scholes_ispc(uniform float Sa[], uniform float Xa[], uniform float Ta[],
uniform float ra[], uniform float va[],
uniform float result[], uniform int count) {
foreach (i = 0 ... count) {
float S = Sa[i], X = Xa[i], T = Ta[i], r = ra[i], v = va[i];
float d1 = (log(S/X) + (r + v * v * .5f) * T) / (v * sqrt(T));
float d2 = d1 - v * sqrt(T);
result[i] = S * CND(d1) - X * exp(-r * T) * CND(d2);
}
}
static inline float
binomial_put(float S, float X, float T, float r, float v) {
float V[BINOMIAL_NUM];
float dt = T / BINOMIAL_NUM;
float u = exp(v * sqrt(dt));
float d = 1. / u;
float disc = exp(r * dt);
float Pu = (disc - d) / (u - d);
for (uniform int j = 0; j < BINOMIAL_NUM; ++j) {
float upow = pow(u, (float)(2*j-BINOMIAL_NUM));
V[j] = max(0., X - S * upow);
}
for (uniform int j = BINOMIAL_NUM-1; j >= 0; --j)
for (uniform int k = 0; k < j; ++k)
V[k] = ((1 - Pu) * V[k] + Pu * V[k + 1]) / disc;
return V[0];
}
export void
binomial_put_ispc(uniform float Sa[], uniform float Xa[], uniform float Ta[],
uniform float ra[], uniform float va[],
uniform float result[], uniform int count) {
foreach (i = 0 ... count) {
float S = Sa[i], X = Xa[i], T = Ta[i], r = ra[i], v = va[i];
result[i] = binomial_put(S, X, T, r, v);
}
}
task void
binomial_task(uniform float Sa[], uniform float Xa[],
uniform float Ta[], uniform float ra[],
uniform float va[], uniform float result[],
uniform int count) {
uniform int first = taskIndex * (count/taskCount);
uniform int last = min(count, (int)((taskIndex+1) * (count/taskCount)));
foreach (i = first ... last) {
float S = Sa[i], X = Xa[i], T = Ta[i], r = ra[i], v = va[i];
result[i] = binomial_put(S, X, T, r, v);
}
}
export void
binomial_put_ispc_tasks(uniform float Sa[], uniform float Xa[],
uniform float Ta[], uniform float ra[],
uniform float va[], uniform float result[],
uniform int count) {
uniform int nTasks = max((int)64, (int)count/16384);
launch[nTasks] binomial_task(Sa, Xa, Ta, ra, va, result, count);
}

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examples_cuda/options/options_defs.h Normal file
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/*
Copyright (c) 2010-2011, Intel 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 Intel 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 AND CONTRIBUTORS "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.
*/
#ifndef OPTIONS_DEFS_H
#define OPTIONS_DEFS_H 1
#define BINOMIAL_NUM 64
#endif // OPTIONS_DEFS_H

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examples_cuda/options/options_serial.cpp Normal file
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/*
Copyright (c) 2010-2011, Intel 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 Intel 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 AND CONTRIBUTORS "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.
*/
#ifdef _MSC_VER
#define _CRT_SECURE_NO_WARNINGS
#define NOMINMAX
#pragma warning (disable: 4244)
#pragma warning (disable: 4305)
#endif
#include "options_defs.h"
#include <math.h>
#include <algorithm>
// Cumulative normal distribution function
static inline float
CND(float X) {
float L = fabsf(X);
float k = 1.f / (1.f + 0.2316419f * L);
float k2 = k*k;
float k3 = k2*k;
float k4 = k2*k2;
float k5 = k3*k2;
const float invSqrt2Pi = 0.39894228040f;
float w = (0.31938153f * k - 0.356563782f * k2 + 1.781477937f * k3 +
-1.821255978f * k4 + 1.330274429f * k5);
w *= invSqrt2Pi * expf(-L * L * .5f);
if (X > 0.f)
w = 1.f - w;
return w;
}
void
black_scholes_serial(float Sa[], float Xa[], float Ta[],
float ra[], float va[],
float result[], int count) {
for (int i = 0; i < count; ++i) {
float S = Sa[i], X = Xa[i];
float T = Ta[i], r = ra[i];
float v = va[i];
float d1 = (logf(S/X) + (r + v * v * .5f) * T) / (v * sqrtf(T));
float d2 = d1 - v * sqrtf(T);
result[i] = S * CND(d1) - X * expf(-r * T) * CND(d2);
}
}
void
binomial_put_serial(float Sa[], float Xa[], float Ta[],
float ra[], float va[],
float result[], int count) {
float V[BINOMIAL_NUM];
for (int i = 0; i < count; ++i) {
float S = Sa[i], X = Xa[i];
float T = Ta[i], r = ra[i];
float v = va[i];
float dt = T / BINOMIAL_NUM;
float u = expf(v * sqrtf(dt));
float d = 1.f / u;
float disc = expf(r * dt);
float Pu = (disc - d) / (u - d);
for (int j = 0; j < BINOMIAL_NUM; ++j) {
float upow = powf(u, (float)(2*j-BINOMIAL_NUM));
V[j] = std::max(0.f, X - S * upow);
}
for (int j = BINOMIAL_NUM-1; j >= 0; --j)
for (int k = 0; k < j; ++k)
V[k] = ((1 - Pu) * V[k] + Pu * V[k + 1]) / disc;
result[i] = V[0];
}
}