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Apply consistent code formatting across the repo. Add clang-format and pre-commit hooks.

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Rob Armstrong
2025-03-27 10:30:07 -07:00
parent 2cd58fbc9a
commit ceab6e8bcc
782 changed files with 107230 additions and 106548 deletions
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331
Samples/5_Domain_Specific/BlackScholes/BlackScholes.cu
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@@ -31,16 +31,20 @@
* See supplied whitepaper for more explanations.
*/
#include <helper_functions.h> // helper functions for string parsing
#include <helper_cuda.h> // helper functions CUDA error checking and initialization
#include <helper_cuda.h> // helper functions CUDA error checking and initialization
#include <helper_functions.h> // helper functions for string parsing
////////////////////////////////////////////////////////////////////////////////
// Process an array of optN options on CPU
////////////////////////////////////////////////////////////////////////////////
extern "C" void BlackScholesCPU(float *h_CallResult, float *h_PutResult,
float *h_StockPrice, float *h_OptionStrike,
float *h_OptionYears, float Riskfree,
float Volatility, int optN);
extern "C" void BlackScholesCPU(float *h_CallResult,
float *h_PutResult,
float *h_StockPrice,
float *h_OptionStrike,
float *h_OptionYears,
float Riskfree,
float Volatility,
int optN);
////////////////////////////////////////////////////////////////////////////////
// Process an array of OptN options on GPU
@@ -51,193 +55,192 @@ extern "C" void BlackScholesCPU(float *h_CallResult, float *h_PutResult,
// Helper function, returning uniformly distributed
// random float in [low, high] range
////////////////////////////////////////////////////////////////////////////////
float RandFloat(float low, float high) {
float t = (float)rand() / (float)RAND_MAX;
return (1.0f - t) * low + t * high;
float RandFloat(float low, float high)
{
float t = (float)rand() / (float)RAND_MAX;
return (1.0f - t) * low + t * high;
}
////////////////////////////////////////////////////////////////////////////////
// Data configuration
////////////////////////////////////////////////////////////////////////////////
const int OPT_N = 4000000;
const int OPT_N = 4000000;
const int NUM_ITERATIONS = 512;
const int OPT_SZ = OPT_N * sizeof(float);
const float RISKFREE = 0.02f;
const int OPT_SZ = OPT_N * sizeof(float);
const float RISKFREE = 0.02f;
const float VOLATILITY = 0.30f;
#define DIV_UP(a, b) (((a) + (b)-1) / (b))
#define DIV_UP(a, b) (((a) + (b) - 1) / (b))
////////////////////////////////////////////////////////////////////////////////
// Main program
////////////////////////////////////////////////////////////////////////////////
int main(int argc, char **argv) {
// Start logs
printf("[%s] - Starting...\n", argv[0]);
int main(int argc, char **argv)
{
// Start logs
printf("[%s] - Starting...\n", argv[0]);
//'h_' prefix - CPU (host) memory space
float
// Results calculated by CPU for reference
*h_CallResultCPU,
*h_PutResultCPU,
// CPU copy of GPU results
*h_CallResultGPU, *h_PutResultGPU,
// CPU instance of input data
*h_StockPrice, *h_OptionStrike, *h_OptionYears;
//'h_' prefix - CPU (host) memory space
float
// Results calculated by CPU for reference
*h_CallResultCPU,
*h_PutResultCPU,
// CPU copy of GPU results
*h_CallResultGPU, *h_PutResultGPU,
// CPU instance of input data
*h_StockPrice, *h_OptionStrike, *h_OptionYears;
//'d_' prefix - GPU (device) memory space
float
// Results calculated by GPU
*d_CallResult,
*d_PutResult,
// GPU instance of input data
*d_StockPrice, *d_OptionStrike, *d_OptionYears;
//'d_' prefix - GPU (device) memory space
float
// Results calculated by GPU
*d_CallResult,
*d_PutResult,
// GPU instance of input data
*d_StockPrice, *d_OptionStrike, *d_OptionYears;
double delta, ref, sum_delta, sum_ref, max_delta, L1norm, gpuTime;
double delta, ref, sum_delta, sum_ref, max_delta, L1norm, gpuTime;
StopWatchInterface *hTimer = NULL;
int i;
StopWatchInterface *hTimer = NULL;
int i;
findCudaDevice(argc, (const char **)argv);
findCudaDevice(argc, (const char **)argv);
sdkCreateTimer(&hTimer);
sdkCreateTimer(&hTimer);
printf("Initializing data...\n");
printf("...allocating CPU memory for options.\n");
h_CallResultCPU = (float *)malloc(OPT_SZ);
h_PutResultCPU = (float *)malloc(OPT_SZ);
h_CallResultGPU = (float *)malloc(OPT_SZ);
h_PutResultGPU = (float *)malloc(OPT_SZ);
h_StockPrice = (float *)malloc(OPT_SZ);
h_OptionStrike = (float *)malloc(OPT_SZ);
h_OptionYears = (float *)malloc(OPT_SZ);
printf("Initializing data...\n");
printf("...allocating CPU memory for options.\n");
h_CallResultCPU = (float *)malloc(OPT_SZ);
h_PutResultCPU = (float *)malloc(OPT_SZ);
h_CallResultGPU = (float *)malloc(OPT_SZ);
h_PutResultGPU = (float *)malloc(OPT_SZ);
h_StockPrice = (float *)malloc(OPT_SZ);
h_OptionStrike = (float *)malloc(OPT_SZ);
h_OptionYears = (float *)malloc(OPT_SZ);
printf("...allocating GPU memory for options.\n");
checkCudaErrors(cudaMalloc((void **)&d_CallResult, OPT_SZ));
checkCudaErrors(cudaMalloc((void **)&d_PutResult, OPT_SZ));
checkCudaErrors(cudaMalloc((void **)&d_StockPrice, OPT_SZ));
checkCudaErrors(cudaMalloc((void **)&d_OptionStrike, OPT_SZ));
checkCudaErrors(cudaMalloc((void **)&d_OptionYears, OPT_SZ));
printf("...allocating GPU memory for options.\n");
checkCudaErrors(cudaMalloc((void **)&d_CallResult, OPT_SZ));
checkCudaErrors(cudaMalloc((void **)&d_PutResult, OPT_SZ));
checkCudaErrors(cudaMalloc((void **)&d_StockPrice, OPT_SZ));
checkCudaErrors(cudaMalloc((void **)&d_OptionStrike, OPT_SZ));
checkCudaErrors(cudaMalloc((void **)&d_OptionYears, OPT_SZ));
printf("...generating input data in CPU mem.\n");
srand(5347);
printf("...generating input data in CPU mem.\n");
srand(5347);
// Generate options set
for (i = 0; i < OPT_N; i++) {
h_CallResultCPU[i] = 0.0f;
h_PutResultCPU[i] = -1.0f;
h_StockPrice[i] = RandFloat(5.0f, 30.0f);
h_OptionStrike[i] = RandFloat(1.0f, 100.0f);
h_OptionYears[i] = RandFloat(0.25f, 10.0f);
}
printf("...copying input data to GPU mem.\n");
// Copy options data to GPU memory for further processing
checkCudaErrors(
cudaMemcpy(d_StockPrice, h_StockPrice, OPT_SZ, cudaMemcpyHostToDevice));
checkCudaErrors(cudaMemcpy(d_OptionStrike, h_OptionStrike, OPT_SZ,
cudaMemcpyHostToDevice));
checkCudaErrors(
cudaMemcpy(d_OptionYears, h_OptionYears, OPT_SZ, cudaMemcpyHostToDevice));
printf("Data init done.\n\n");
printf("Executing Black-Scholes GPU kernel (%i iterations)...\n",
NUM_ITERATIONS);
checkCudaErrors(cudaDeviceSynchronize());
sdkResetTimer(&hTimer);
sdkStartTimer(&hTimer);
for (i = 0; i < NUM_ITERATIONS; i++) {
BlackScholesGPU<<<DIV_UP((OPT_N / 2), 128), 128 /*480, 128*/>>>(
(float2 *)d_CallResult, (float2 *)d_PutResult, (float2 *)d_StockPrice,
(float2 *)d_OptionStrike, (float2 *)d_OptionYears, RISKFREE, VOLATILITY,
OPT_N);
getLastCudaError("BlackScholesGPU() execution failed\n");
}
checkCudaErrors(cudaDeviceSynchronize());
sdkStopTimer(&hTimer);
gpuTime = sdkGetTimerValue(&hTimer) / NUM_ITERATIONS;
// Both call and put is calculated
printf("Options count : %i \n", 2 * OPT_N);
printf("BlackScholesGPU() time : %f msec\n", gpuTime);
printf("Effective memory bandwidth: %f GB/s\n",
((double)(5 * OPT_N * sizeof(float)) * 1E-9) / (gpuTime * 1E-3));
printf("Gigaoptions per second : %f \n\n",
((double)(2 * OPT_N) * 1E-9) / (gpuTime * 1E-3));
printf(
"BlackScholes, Throughput = %.4f GOptions/s, Time = %.5f s, Size = %u "
"options, NumDevsUsed = %u, Workgroup = %u\n",
(((double)(2.0 * OPT_N) * 1.0E-9) / (gpuTime * 1.0E-3)), gpuTime * 1e-3,
(2 * OPT_N), 1, 128);
printf("\nReading back GPU results...\n");
// Read back GPU results to compare them to CPU results
checkCudaErrors(cudaMemcpy(h_CallResultGPU, d_CallResult, OPT_SZ,
cudaMemcpyDeviceToHost));
checkCudaErrors(
cudaMemcpy(h_PutResultGPU, d_PutResult, OPT_SZ, cudaMemcpyDeviceToHost));
printf("Checking the results...\n");
printf("...running CPU calculations.\n\n");
// Calculate options values on CPU
BlackScholesCPU(h_CallResultCPU, h_PutResultCPU, h_StockPrice, h_OptionStrike,
h_OptionYears, RISKFREE, VOLATILITY, OPT_N);
printf("Comparing the results...\n");
// Calculate max absolute difference and L1 distance
// between CPU and GPU results
sum_delta = 0;
sum_ref = 0;
max_delta = 0;
for (i = 0; i < OPT_N; i++) {
ref = h_CallResultCPU[i];
delta = fabs(h_CallResultCPU[i] - h_CallResultGPU[i]);
if (delta > max_delta) {
max_delta = delta;
// Generate options set
for (i = 0; i < OPT_N; i++) {
h_CallResultCPU[i] = 0.0f;
h_PutResultCPU[i] = -1.0f;
h_StockPrice[i] = RandFloat(5.0f, 30.0f);
h_OptionStrike[i] = RandFloat(1.0f, 100.0f);
h_OptionYears[i] = RandFloat(0.25f, 10.0f);
}
sum_delta += delta;
sum_ref += fabs(ref);
}
printf("...copying input data to GPU mem.\n");
// Copy options data to GPU memory for further processing
checkCudaErrors(cudaMemcpy(d_StockPrice, h_StockPrice, OPT_SZ, cudaMemcpyHostToDevice));
checkCudaErrors(cudaMemcpy(d_OptionStrike, h_OptionStrike, OPT_SZ, cudaMemcpyHostToDevice));
checkCudaErrors(cudaMemcpy(d_OptionYears, h_OptionYears, OPT_SZ, cudaMemcpyHostToDevice));
printf("Data init done.\n\n");
L1norm = sum_delta / sum_ref;
printf("L1 norm: %E\n", L1norm);
printf("Max absolute error: %E\n\n", max_delta);
printf("Executing Black-Scholes GPU kernel (%i iterations)...\n", NUM_ITERATIONS);
checkCudaErrors(cudaDeviceSynchronize());
sdkResetTimer(&hTimer);
sdkStartTimer(&hTimer);
printf("Shutting down...\n");
printf("...releasing GPU memory.\n");
checkCudaErrors(cudaFree(d_OptionYears));
checkCudaErrors(cudaFree(d_OptionStrike));
checkCudaErrors(cudaFree(d_StockPrice));
checkCudaErrors(cudaFree(d_PutResult));
checkCudaErrors(cudaFree(d_CallResult));
for (i = 0; i < NUM_ITERATIONS; i++) {
BlackScholesGPU<<<DIV_UP((OPT_N / 2), 128), 128 /*480, 128*/>>>((float2 *)d_CallResult,
(float2 *)d_PutResult,
(float2 *)d_StockPrice,
(float2 *)d_OptionStrike,
(float2 *)d_OptionYears,
RISKFREE,
VOLATILITY,
OPT_N);
getLastCudaError("BlackScholesGPU() execution failed\n");
}
printf("...releasing CPU memory.\n");
free(h_OptionYears);
free(h_OptionStrike);
free(h_StockPrice);
free(h_PutResultGPU);
free(h_CallResultGPU);
free(h_PutResultCPU);
free(h_CallResultCPU);
sdkDeleteTimer(&hTimer);
printf("Shutdown done.\n");
checkCudaErrors(cudaDeviceSynchronize());
sdkStopTimer(&hTimer);
gpuTime = sdkGetTimerValue(&hTimer) / NUM_ITERATIONS;
printf("\n[BlackScholes] - Test Summary\n");
// Both call and put is calculated
printf("Options count : %i \n", 2 * OPT_N);
printf("BlackScholesGPU() time : %f msec\n", gpuTime);
printf("Effective memory bandwidth: %f GB/s\n", ((double)(5 * OPT_N * sizeof(float)) * 1E-9) / (gpuTime * 1E-3));
printf("Gigaoptions per second : %f \n\n", ((double)(2 * OPT_N) * 1E-9) / (gpuTime * 1E-3));
if (L1norm > 1e-6) {
printf("Test failed!\n");
exit(EXIT_FAILURE);
}
printf("BlackScholes, Throughput = %.4f GOptions/s, Time = %.5f s, Size = %u "
"options, NumDevsUsed = %u, Workgroup = %u\n",
(((double)(2.0 * OPT_N) * 1.0E-9) / (gpuTime * 1.0E-3)),
gpuTime * 1e-3,
(2 * OPT_N),
1,
128);
printf(
"\nNOTE: The CUDA Samples are not meant for performance measurements. "
"Results may vary when GPU Boost is enabled.\n\n");
printf("Test passed\n");
exit(EXIT_SUCCESS);
printf("\nReading back GPU results...\n");
// Read back GPU results to compare them to CPU results
checkCudaErrors(cudaMemcpy(h_CallResultGPU, d_CallResult, OPT_SZ, cudaMemcpyDeviceToHost));
checkCudaErrors(cudaMemcpy(h_PutResultGPU, d_PutResult, OPT_SZ, cudaMemcpyDeviceToHost));
printf("Checking the results...\n");
printf("...running CPU calculations.\n\n");
// Calculate options values on CPU
BlackScholesCPU(
h_CallResultCPU, h_PutResultCPU, h_StockPrice, h_OptionStrike, h_OptionYears, RISKFREE, VOLATILITY, OPT_N);
printf("Comparing the results...\n");
// Calculate max absolute difference and L1 distance
// between CPU and GPU results
sum_delta = 0;
sum_ref = 0;
max_delta = 0;
for (i = 0; i < OPT_N; i++) {
ref = h_CallResultCPU[i];
delta = fabs(h_CallResultCPU[i] - h_CallResultGPU[i]);
if (delta > max_delta) {
max_delta = delta;
}
sum_delta += delta;
sum_ref += fabs(ref);
}
L1norm = sum_delta / sum_ref;
printf("L1 norm: %E\n", L1norm);
printf("Max absolute error: %E\n\n", max_delta);
printf("Shutting down...\n");
printf("...releasing GPU memory.\n");
checkCudaErrors(cudaFree(d_OptionYears));
checkCudaErrors(cudaFree(d_OptionStrike));
checkCudaErrors(cudaFree(d_StockPrice));
checkCudaErrors(cudaFree(d_PutResult));
checkCudaErrors(cudaFree(d_CallResult));
printf("...releasing CPU memory.\n");
free(h_OptionYears);
free(h_OptionStrike);
free(h_StockPrice);
free(h_PutResultGPU);
free(h_CallResultGPU);
free(h_PutResultCPU);
free(h_CallResultCPU);
sdkDeleteTimer(&hTimer);
printf("Shutdown done.\n");
printf("\n[BlackScholes] - Test Summary\n");
if (L1norm > 1e-6) {
printf("Test failed!\n");
exit(EXIT_FAILURE);
}
printf("\nNOTE: The CUDA Samples are not meant for performance measurements. "
"Results may vary when GPU Boost is enabled.\n\n");
printf("Test passed\n");
exit(EXIT_SUCCESS);
}

86
Samples/5_Domain_Specific/BlackScholes/BlackScholes_gold.cpp
View File

@@ -30,57 +30,69 @@
////////////////////////////////////////////////////////////////////////////////
// Polynomial approximation of cumulative normal distribution function
////////////////////////////////////////////////////////////////////////////////
static double CND(double d) {
const double A1 = 0.31938153;
const double A2 = -0.356563782;
const double A3 = 1.781477937;
const double A4 = -1.821255978;
const double A5 = 1.330274429;
const double RSQRT2PI = 0.39894228040143267793994605993438;
static double CND(double d)
{
const double A1 = 0.31938153;
const double A2 = -0.356563782;
const double A3 = 1.781477937;
const double A4 = -1.821255978;
const double A5 = 1.330274429;
const double RSQRT2PI = 0.39894228040143267793994605993438;
double K = 1.0 / (1.0 + 0.2316419 * fabs(d));
double K = 1.0 / (1.0 + 0.2316419 * fabs(d));
double cnd = RSQRT2PI * exp(-0.5 * d * d) *
(K * (A1 + K * (A2 + K * (A3 + K * (A4 + K * A5)))));
double cnd = RSQRT2PI * exp(-0.5 * d * d) * (K * (A1 + K * (A2 + K * (A3 + K * (A4 + K * A5)))));
if (d > 0) cnd = 1.0 - cnd;
if (d > 0)
cnd = 1.0 - cnd;
return cnd;
return cnd;
}
////////////////////////////////////////////////////////////////////////////////
// Black-Scholes formula for both call and put
////////////////////////////////////////////////////////////////////////////////
static void BlackScholesBodyCPU(float &callResult, float &putResult,
float Sf, // Stock price
float Xf, // Option strike
float Tf, // Option years
float Rf, // Riskless rate
float Vf // Volatility rate
) {
double S = Sf, X = Xf, T = Tf, R = Rf, V = Vf;
static void BlackScholesBodyCPU(float &callResult,
float &putResult,
float Sf, // Stock price
float Xf, // Option strike
float Tf, // Option years
float Rf, // Riskless rate
float Vf // Volatility rate
)
{
double S = Sf, X = Xf, T = Tf, R = Rf, V = Vf;
double sqrtT = sqrt(T);
double d1 = (log(S / X) + (R + 0.5 * V * V) * T) / (V * sqrtT);
double d2 = d1 - V * sqrtT;
double CNDD1 = CND(d1);
double CNDD2 = CND(d2);
double sqrtT = sqrt(T);
double d1 = (log(S / X) + (R + 0.5 * V * V) * T) / (V * sqrtT);
double d2 = d1 - V * sqrtT;
double CNDD1 = CND(d1);
double CNDD2 = CND(d2);
// Calculate Call and Put simultaneously
double expRT = exp(-R * T);
callResult = (float)(S * CNDD1 - X * expRT * CNDD2);
putResult = (float)(X * expRT * (1.0 - CNDD2) - S * (1.0 - CNDD1));
// Calculate Call and Put simultaneously
double expRT = exp(-R * T);
callResult = (float)(S * CNDD1 - X * expRT * CNDD2);
putResult = (float)(X * expRT * (1.0 - CNDD2) - S * (1.0 - CNDD1));
}
////////////////////////////////////////////////////////////////////////////////
// Process an array of optN options
////////////////////////////////////////////////////////////////////////////////
extern "C" void BlackScholesCPU(float *h_CallResult, float *h_PutResult,
float *h_StockPrice, float *h_OptionStrike,
float *h_OptionYears, float Riskfree,
float Volatility, int optN) {
for (int opt = 0; opt < optN; opt++)
BlackScholesBodyCPU(h_CallResult[opt], h_PutResult[opt], h_StockPrice[opt],
h_OptionStrike[opt], h_OptionYears[opt], Riskfree,
Volatility);
extern "C" void BlackScholesCPU(float *h_CallResult,
float *h_PutResult,
float *h_StockPrice,
float *h_OptionStrike,
float *h_OptionYears,
float Riskfree,
float Volatility,
int optN)
{
for (int opt = 0; opt < optN; opt++)
BlackScholesBodyCPU(h_CallResult[opt],
h_PutResult[opt],
h_StockPrice[opt],
h_OptionStrike[opt],
h_OptionYears[opt],
Riskfree,
Volatility);
}

125
Samples/5_Domain_Specific/BlackScholes/BlackScholes_kernel.cuh
View File

@@ -28,79 +28,92 @@
////////////////////////////////////////////////////////////////////////////////
// Polynomial approximation of cumulative normal distribution function
////////////////////////////////////////////////////////////////////////////////
__device__ inline float cndGPU(float d) {
const float A1 = 0.31938153f;
const float A2 = -0.356563782f;
const float A3 = 1.781477937f;
const float A4 = -1.821255978f;
const float A5 = 1.330274429f;
const float RSQRT2PI = 0.39894228040143267793994605993438f;
__device__ inline float cndGPU(float d)
{
const float A1 = 0.31938153f;
const float A2 = -0.356563782f;
const float A3 = 1.781477937f;
const float A4 = -1.821255978f;
const float A5 = 1.330274429f;
const float RSQRT2PI = 0.39894228040143267793994605993438f;
float K = __fdividef(1.0f, (1.0f + 0.2316419f * fabsf(d)));
float K = __fdividef(1.0f, (1.0f + 0.2316419f * fabsf(d)));
float cnd = RSQRT2PI * __expf(-0.5f * d * d) *
(K * (A1 + K * (A2 + K * (A3 + K * (A4 + K * A5)))));
float cnd = RSQRT2PI * __expf(-0.5f * d * d) * (K * (A1 + K * (A2 + K * (A3 + K * (A4 + K * A5)))));
if (d > 0) cnd = 1.0f - cnd;
if (d > 0)
cnd = 1.0f - cnd;
return cnd;
return cnd;
}
////////////////////////////////////////////////////////////////////////////////
// Black-Scholes formula for both call and put
////////////////////////////////////////////////////////////////////////////////
__device__ inline void BlackScholesBodyGPU(float &CallResult, float &PutResult,
float S, // Stock price
float X, // Option strike
float T, // Option years
float R, // Riskless rate
float V // Volatility rate
) {
float sqrtT, expRT;
float d1, d2, CNDD1, CNDD2;
__device__ inline void BlackScholesBodyGPU(float &CallResult,
float &PutResult,
float S, // Stock price
float X, // Option strike
float T, // Option years
float R, // Riskless rate
float V // Volatility rate
)
{
float sqrtT, expRT;
float d1, d2, CNDD1, CNDD2;
sqrtT = __fdividef(1.0F, rsqrtf(T));
d1 = __fdividef(__logf(S / X) + (R + 0.5f * V * V) * T, V * sqrtT);
d2 = d1 - V * sqrtT;
sqrtT = __fdividef(1.0F, rsqrtf(T));
d1 = __fdividef(__logf(S / X) + (R + 0.5f * V * V) * T, V * sqrtT);
d2 = d1 - V * sqrtT;
CNDD1 = cndGPU(d1);
CNDD2 = cndGPU(d2);
CNDD1 = cndGPU(d1);
CNDD2 = cndGPU(d2);
// Calculate Call and Put simultaneously
expRT = __expf(-R * T);
CallResult = S * CNDD1 - X * expRT * CNDD2;
PutResult = X * expRT * (1.0f - CNDD2) - S * (1.0f - CNDD1);
// Calculate Call and Put simultaneously
expRT = __expf(-R * T);
CallResult = S * CNDD1 - X * expRT * CNDD2;
PutResult = X * expRT * (1.0f - CNDD2) - S * (1.0f - CNDD1);
}
////////////////////////////////////////////////////////////////////////////////
// Process an array of optN options on GPU
////////////////////////////////////////////////////////////////////////////////
__launch_bounds__(128) __global__
void BlackScholesGPU(float2 *__restrict d_CallResult,
float2 *__restrict d_PutResult,
float2 *__restrict d_StockPrice,
float2 *__restrict d_OptionStrike,
float2 *__restrict d_OptionYears, float Riskfree,
float Volatility, int optN) {
////Thread index
// const int tid = blockDim.x * blockIdx.x + threadIdx.x;
////Total number of threads in execution grid
// const int THREAD_N = blockDim.x * gridDim.x;
__launch_bounds__(128) __global__ void BlackScholesGPU(float2 *__restrict d_CallResult,
float2 *__restrict d_PutResult,
float2 *__restrict d_StockPrice,
float2 *__restrict d_OptionStrike,
float2 *__restrict d_OptionYears,
float Riskfree,
float Volatility,
int optN)
{
////Thread index
// const int tid = blockDim.x * blockIdx.x + threadIdx.x;
////Total number of threads in execution grid
// const int THREAD_N = blockDim.x * gridDim.x;
const int opt = blockDim.x * blockIdx.x + threadIdx.x;
const int opt = blockDim.x * blockIdx.x + threadIdx.x;
// Calculating 2 options per thread to increase ILP (instruction level
// parallelism)
if (opt < (optN / 2)) {
float callResult1, callResult2;
float putResult1, putResult2;
BlackScholesBodyGPU(callResult1, putResult1, d_StockPrice[opt].x,
d_OptionStrike[opt].x, d_OptionYears[opt].x, Riskfree,
Volatility);
BlackScholesBodyGPU(callResult2, putResult2, d_StockPrice[opt].y,
d_OptionStrike[opt].y, d_OptionYears[opt].y, Riskfree,
Volatility);
d_CallResult[opt] = make_float2(callResult1, callResult2);
d_PutResult[opt] = make_float2(putResult1, putResult2);
}
// Calculating 2 options per thread to increase ILP (instruction level
// parallelism)
if (opt < (optN / 2)) {
float callResult1, callResult2;
float putResult1, putResult2;
BlackScholesBodyGPU(callResult1,
putResult1,
d_StockPrice[opt].x,
d_OptionStrike[opt].x,
d_OptionYears[opt].x,
Riskfree,
Volatility);
BlackScholesBodyGPU(callResult2,
putResult2,
d_StockPrice[opt].y,
d_OptionStrike[opt].y,
d_OptionYears[opt].y,
Riskfree,
Volatility);
d_CallResult[opt] = make_float2(callResult1, callResult2);
d_PutResult[opt] = make_float2(putResult1, putResult2);
}
}