static void Main(string[] args)
{
Console.WriteLine("running benchmark for stochastic volatility model on the cpu");
int ni = 10;
double S0 = 100;
int nscen_per_batch = 4096 * 25;
int nbatches = 100;
TimeSpan dt0 = TimeSpan.FromDays(1);
EFloatingPointUnit fpu = EFloatingPointUnit.host;
EFloatingPointPrecision fpp = EFloatingPointPrecision.bit64;
DateTime today = DateTime.Today;
DateTime[] t_k = new DateTime[40];
for (int k = 0; k < 40; k++) t_k[k] = today.AddDays(7 * (k + 1));
DateTime[] t_i = new DateTime[ni];
t_i[0] = today.AddDays(30); t_i[1] = today.AddDays(60);
t_i[2] = today.AddDays(90); t_i[3] = today.AddDays(120);
t_i[4] = today.AddDays(150); t_i[5] = today.AddDays(180);
t_i[6] = today.AddDays(210); t_i[7] = today.AddDays(240);
t_i[8] = today.AddDays(270); t_i[9] = today.AddDays(300);
double[] xpivot_p = new double[7];
double[] xgridspacing_p = new double[7];
xpivot_p[0] = 1; xgridspacing_p[0] = 5;
xpivot_p[1] = 70; xgridspacing_p[1] = 2.5;
xpivot_p[2] = 90; xgridspacing_p[2] = 1;
xpivot_p[3] = 110; xgridspacing_p[3] = 2.5;
xpivot_p[4] = 140; xgridspacing_p[4] = 5;
xpivot_p[5] = 200; xgridspacing_p[5] = 7.5;
xpivot_p[6] = 300; xgridspacing_p[6] = 10;
int nx = 64;
int nr = 8;
double[] rval_r = new double[nr];
rval_r[0] = 0.55;
rval_r[1] = 0.75;
rval_r[2] = 0.90;
rval_r[3] = 1.0;
rval_r[4] = 1.1;
rval_r[5] = 1.3;
rval_r[6] = 1.6;
rval_r[7] = 2.0;
int r0 = 4;
OPModel.Types.CDevice device = new OPModel.Types.CDevice(fpp, fpu, 0);
OPModel.Types.S2DGrid grid = new OPModel.Types.S2DGrid(device, nx, nr, today, t_i, dt0, S0, xpivot_p, xgridspacing_p, rval_r, r0);
double vol = .25;
double lowbeta = 0.5;
double highbeta = 0.5;
double volvol = 0.5;
double volmrr = 0.5;
double volmrl = 3;
double jumpsz_minus = -3.0;
double jumpsz_plus = 0.0;
double[,] taumatrix_ccol = new double[8, 4];
for (int col = 0; col <= 2; col++)
{
taumatrix_ccol[0, col] = vol;
taumatrix_ccol[1, col] = lowbeta;
taumatrix_ccol[2, col] = highbeta;
taumatrix_ccol[3, col] = volvol;
taumatrix_ccol[4, col] = volmrr;
taumatrix_ccol[5, col] = volmrl;
taumatrix_ccol[6, col] = jumpsz_minus;
taumatrix_ccol[7, col] = jumpsz_plus;
}
double[] ir_i = new double[ni];
double[] df_i = new double[ni];
for (int i = 0; i < ni; i++)
{
ir_i[i] = 0.05;
if (i == 0) df_i[0] = Math.Exp(-ir_i[i] * (t_i[0] - grid.today).Days / 365.25);
else df_i[i] = df_i[i - 1] * Math.Exp(-ir_i[i] * (t_i[i] - t_i[i - 1]).Days / 365.25);
}
CStopWatch sw = new CStopWatch();
CSVModel model = new CSVModel(grid, "DCSV1F", df_i);
model.mkgen(taumatrix_ccol, null);
model.make_mc_plan(nscen_per_batch, nbatches, t_k);
model.reset_flop_counter();
double time = sw.Peek();
sw.Reset();
model.exe_mc_plan();
time = sw.Peek();
double nflops = model.cpu_nflops;
double gigaflops_per_second = nflops / (1000000000d * time);
Console.WriteLine("blas performance: " + String.Format("{0:0.0}", gigaflops_per_second) + " GF/sec");
CMCEvaluator evaluator = new emptyEvaluator();
double[] payoff_a = new double[nscen_per_batch * model.mcplan.nth];
model.host_d_mc_init();
sw.Reset();
unsafe
{
model.host_d_mc_run1f(payoff_a, evaluator);
}
time = sw.Peek();
double nevals = (double)t_k.Length * (double)nbatches * (double)nscen_per_batch;
double milion_evals_per_second = nevals / (1000000 * time);
Console.WriteLine("mc performance: " + String.Format("{0:0.0}", milion_evals_per_second) + " milion eval/sec");
Console.Read();
}
public static void run_benchmark_gpu_sgsv1f(uint dev)
{
Console.WriteLine("running sgsv1f, device " + dev);
int ni = 10;
double S0 = 100;
int nscen_per_batch = 4096 * 25;
int nbatches = 100;
TimeSpan dt0 = TimeSpan.FromDays(1);
EFloatingPointUnit fpu = EFloatingPointUnit.device;
EFloatingPointPrecision fpp = EFloatingPointPrecision.bit32;
DateTime today = DateTime.Today;
DateTime[] t_k = new DateTime[40];
for (int k = 0; k < 40; k++) t_k[k] = today.AddDays(7 * (k + 1));
DateTime[] t_i = new DateTime[ni];
t_i[0] = today.AddDays(30); t_i[1] = today.AddDays(60);
t_i[2] = today.AddDays(90); t_i[3] = today.AddDays(120);
t_i[4] = today.AddDays(150); t_i[5] = today.AddDays(180);
t_i[6] = today.AddDays(210); t_i[7] = today.AddDays(240);
t_i[8] = today.AddDays(270); t_i[9] = today.AddDays(300);
double[] xpivot_p = new double[7];
double[] xgridspacing_p = new double[7];
xpivot_p[0] = 1; xgridspacing_p[0] = 5;
xpivot_p[1] = 70; xgridspacing_p[1] = 2.5;
xpivot_p[2] = 90; xgridspacing_p[2] = 1;
xpivot_p[3] = 110; xgridspacing_p[3] = 2.5;
xpivot_p[4] = 140; xgridspacing_p[4] = 5;
xpivot_p[5] = 200; xgridspacing_p[5] = 7.5;
xpivot_p[6] = 300; xgridspacing_p[6] = 10;
int nx = 64;
int nr = 8;
double[] rval_r = new double[nr];
rval_r[0] = 0.55;
rval_r[1] = 0.75;
rval_r[2] = 0.90;
rval_r[3] = 1.0;
rval_r[4] = 1.1;
rval_r[5] = 1.3;
rval_r[6] = 1.6;
rval_r[7] = 2.0;
int r0 = 4;
OPModel.Types.CDevice device = new OPModel.Types.CDevice(fpp, fpu, 0);
OPModel.Types.S2DGrid grid = new OPModel.Types.S2DGrid(device, nx, nr, today, t_i, dt0, S0, xpivot_p, xgridspacing_p, rval_r, r0);
double vol = .25;
double lowbeta = 0.5;
double highbeta = 0.5;
double volvol = 0.5;
double volmrr = 0.5;
double volmrl = 3;
double jumpsz_minus = -3.0;
double jumpsz_plus = 0.0;
double[,] taumatrix_ccol = new double[8, 4];
for (int col = 0; col <= 2; col++)
{
taumatrix_ccol[0, col] = vol;
taumatrix_ccol[1, col] = lowbeta;
taumatrix_ccol[2, col] = highbeta;
taumatrix_ccol[3, col] = volvol;
taumatrix_ccol[4, col] = volmrr;
taumatrix_ccol[5, col] = volmrl;
taumatrix_ccol[6, col] = jumpsz_minus;
taumatrix_ccol[7, col] = jumpsz_plus;
}
double[] ir_i = new double[ni];
double[] df_i = new double[ni];
for (int i = 0; i < ni; i++)
{
ir_i[i] = 0.05;
if (i == 0)
df_i[0] = Math.Exp(-ir_i[i] * (t_i[0] - grid.today).Days / 365.25);
else
df_i[i] = df_i[i - 1] * Math.Exp(-ir_i[i] * (t_i[i] - t_i[i - 1]).Days / 365.25);
}
CSVModel model = new CSVModel(grid, "SGSV1F", df_i);
model.mkgen(taumatrix_ccol, null);
model.make_mc_plan(nscen_per_batch, nbatches, t_k);
model.device_thread_synchronize();
CStopWatch sw = new CStopWatch();
sw.Reset();
model.reset_flop_counter();
model.exe_mc_plan();
model.device_thread_synchronize();
double time = sw.Peek();
double nflops = model.gpu_nflops;
double gigaflops_per_second = nflops / (1000000000d * time);
Console.WriteLine("blas performance: " + String.Format("{0:0.0}", gigaflops_per_second) + " GF/sec");
CMCEvaluator evaluator = new emptyEvaluator();
double[] pdf_y = new double[grid.d];
sw.Reset();
if (model.device_mc_init() == 1)
{
Console.WriteLine("device_mc_init() failed on device " + dev + ". Aborting");
return;
}
unsafe
{
model.device_mc_run1f(pdf_y, evaluator);
}
model.device_thread_synchronize();
time = sw.Peek();
double nevals = (double)t_k.Length * (double)nbatches * (double)nscen_per_batch;
double milion_evals_per_second = nevals / (1000000 * time);
int status = opcuda_shutdown();
if (status != 0) throw new ExecutionEngineException();
Console.WriteLine("mc performance: " + String.Format("{0:0.0}", milion_evals_per_second) + " milion eval/sec");
}
