public void VectorBinarySearch()
{
var factory = new NArrayFactory(StorageLocation.Host);
int length = 30000;
int knotPointsLength = 100;
var valuesArray = Enumerable.Range(0, length).Select(i => (double)i / length + 0.5).ToArray();
var values = factory.CreateFromEnumerable(valuesArray);
var xArray = Enumerable.Range(0, knotPointsLength).Select(i => (double)i / knotPointsLength).ToArray();
var yArray = Enumerable.Range(0, knotPointsLength).Select(i => 5 + (double)i / knotPointsLength).ToArray();
NArray x = factory.CreateFromEnumerable(xArray);
NArray y = factory.CreateFromEnumerable(yArray);
var watch = new Stopwatch(); watch.Start();
for (int i = 0; i < 50000; ++i)
{
BinarySearch(xArray, yArray, valuesArray);
}
Console.WriteLine("Baseline sequential");
Console.WriteLine(watch.ElapsedMilliseconds); watch.Restart();
for (int i = 0; i < 100; ++i)
{
var left = NArrayFactory.CreateConstantLike(values, 0);
var right = NArrayFactory.CreateConstantLike(values, x.Length - 1);
var mid = (left + right) >> 1;
//// we are going to stop when right - left = 1
//// for the vector version, we cannot allow the break condition to be different for different
//// vector elements
int elements = (x.Length - 1) << 1;
while (elements > 1)
{
var active = (right - left) > 1;
var midValue = x[mid];
right[midValue >= values && active] = mid;
// or alternate form:
//right.Assign(
// () => midValue >= values && active,
// () => mid);
// A conditional in a CUDA kernel would cause the evaluation of both branches
// But we can be more efficient on CPU (e.g. mask vector indexing)
left[midValue < values && active] = mid;
mid = left + right >> 1;
elements = elements >> 1;
}
}
Console.WriteLine("Vector sequential");
Console.WriteLine(watch.ElapsedMilliseconds); watch.Restart();
//check!
//(right - left).DebugDataView.ToArray()
}
public void VectorBinarySearch()
{
var factory = new NArrayFactory(StorageLocation.Host);
int length = 30000;
int knotPointsLength = 100;
var valuesArray = Enumerable.Range(0, length).Select(i => (double)i / length + 0.5).ToArray();
var values = factory.CreateFromEnumerable(valuesArray);
var xArray = Enumerable.Range(0, knotPointsLength).Select(i => (double)i / knotPointsLength).ToArray();
var yArray = Enumerable.Range(0, knotPointsLength).Select(i => 5 + (double)i / knotPointsLength).ToArray();
NArray x = factory.CreateFromEnumerable(xArray);
NArray y = factory.CreateFromEnumerable(yArray);
var watch = new Stopwatch(); watch.Start();
for (int i = 0; i < 50000; ++i)
{
BinarySearch(xArray, yArray, valuesArray);
}
Console.WriteLine("Baseline sequential");
Console.WriteLine(watch.ElapsedMilliseconds); watch.Restart();
for (int i = 0; i < 100; ++i)
{
var left = NArrayFactory.CreateConstantLike(values, 0);
var right = NArrayFactory.CreateConstantLike(values, x.Length - 1);
var mid = (left + right) >> 1;
//// we are going to stop when right - left = 1
//// for the vector version, we cannot allow the break condition to be different for different
//// vector elements
int elements = (x.Length - 1) << 1;
while (elements > 1)
{
var active = (right - left) > 1;
var midValue = x[mid];
right[midValue >= values && active] = mid;
// or alternate form:
//right.Assign(
// () => midValue >= values && active,
// () => mid);
// A conditional in a CUDA kernel would cause the evaluation of both branches
// But we can be more efficient on CPU (e.g. mask vector indexing)
left[midValue < values && active] = mid;
mid = left + right >> 1;
elements = elements >> 1;
}
}
Console.WriteLine("Vector sequential");
Console.WriteLine(watch.ElapsedMilliseconds); watch.Restart();
//check!
//(right - left).DebugDataView.ToArray()
}
public void TestCorrelation()
{
var factory = new NArrayFactory(StorageLocation.Host);
var a = factory.CreateNArray(new double[] { 0.32, 0.91, -0.32, -0.25 });
var b = factory.CreateNArray(new double[] { 0.49, 0.75, -0.39, -0.20 });
var correlation = NMath.Correlation(a, b);
Assert.AreEqual(Math.Round(correlation, 12), Math.Round(0.96831734966276, 12));
}
public void TestCorrelation()
{
var factory = new NArrayFactory(StorageLocation.Host);
var a = factory.CreateNArray(new double[] { 0.32, 0.91, -0.32, -0.25 });
var b = factory.CreateNArray(new double[] { 0.49, 0.75, -0.39, -0.20 });
var correlation = NMath.Correlation(a, b);
Assert.AreEqual(Math.Round(correlation, 12), Math.Round(0.96831734966276, 12));
}
public void NearestCorrelation()
{
var factory = new NArrayFactory(StorageLocation.Host);
var correlation = factory.CreateNArray(new double[, ] {
{ 1.0, 0.84, -0.42 },
{ 0.84, 1.0, 0.14 },
{ -0.42, 0.14, 1.0 }
});
var nearestCorrelation = CorrelationHelper.NearestCorrelationMatrix(correlation);
Console.WriteLine(nearestCorrelation.ToString());
}
public void ConditionalExample()
{
int length = 1000;
var factory = new NArrayFactory(StorageLocation.Host);
NArray x = factory.CreateFromEnumerable(Enumerable.Range(0, length).Select(i => (double)i / length));
var y = x > 0.5;
//x[y] = 6;
//var subset = x[y];
//var y = x[x > 0.5];
}
public void ConditionalExample()
{
int length = 1000;
var factory = new NArrayFactory(StorageLocation.Host);
NArray x = factory.CreateFromEnumerable(Enumerable.Range(0, length).Select(i => (double)i / length));
var y = x > 0.5;
//x[y] = 6;
//var subset = x[y];
//var y = x[x > 0.5];
}
public void SimpleDeferredOperationsTest()
{
var location = StorageLocation.Host;
var factory = new NArrayFactory(location);
using (var randomStream =
new RandomNumberStream(location, RandomNumberGeneratorType.MRG32K3A, 111))
{
var normalDistribution = new Normal(randomStream, 0, 1);
var epsilon = factory.CreateNArray(1000, 1);
epsilon.FillRandom(normalDistribution);
var x = epsilon * Math.Sqrt(0.25) * 0.2;
}
}
public void SimpleDeferredOperationsTest()
{
var location = StorageLocation.Host;
var factory = new NArrayFactory(location);
using (var randomStream =
new RandomNumberStream(location, RandomNumberGeneratorType.MRG32K3A, 111))
{
var normalDistribution = new Normal(randomStream, 0, 1);
var epsilon = factory.CreateNArray(1000, 1);
epsilon.FillRandom(normalDistribution);
var x = epsilon * Math.Sqrt(0.25) * 0.2;
}
}
public Context(StorageLocation location, DateTime closeOfBusinessDate)
{
Factory = new NArrayFactory(location);
Settings = new SimulationSettings(closeOfBusinessDate);
}
public void NearestCorrelation()
{
var factory = new NArrayFactory(StorageLocation.Host);
var correlation = factory.CreateNArray(new double[,] {
{ 1.0, 0.84, -0.42},
{ 0.84, 1.0, 0.14},
{ -0.42, 0.14, 1.0}
});
var nearestCorrelation = CorrelationHelper.NearestCorrelationMatrix(correlation);
Console.WriteLine(nearestCorrelation.ToString());
}
public Context(StorageLocation location, DateTime closeOfBusinessDate)
{
Factory = new NArrayFactory(location);
Settings = new SimulationSettings(closeOfBusinessDate);
}
public void SimpleSpeedTest()
{
var factory = new NArrayFactory(StorageLocation.Host);
IntelMathKernelLibrary.SetAccuracyMode(VMLAccuracy.LowAccuracy);
int length = 1024 * 5;
var a = factory.CreateFromEnumerable(Enumerable.Range(0, length).Select(i => (double)i / length));
var a2 = (a.Storage as VectorAccelerator.NArrayStorage.ManagedStorage<double>).Array;
var b = factory.CreateFromEnumerable(Enumerable.Range(3, length).Select(i => (double)i / length));
var b2 = (b.Storage as VectorAccelerator.NArrayStorage.ManagedStorage<double>).Array;
double[] result = null;
NArray resultN = null;
Console.WriteLine("Allocation");
Timeit(
() =>
{
result = new double[length];
});
Console.WriteLine(Environment.NewLine);
result = new double[length];
Console.WriteLine("Managed optimal");
Timeit(
() =>
{
for (int i = 0; i < result.Length; ++i)
//Parallel.For(0, result.Length, (i) =>
{
result[i] = 3 * Math.Log(Math.Exp(a2[i]) * Math.Exp(b2[i]));
}
//);
});
Console.WriteLine(Environment.NewLine);
var vectorOptions = new VectorAccelerator.DeferredExecution.VectorExecutionOptions();
vectorOptions.MultipleThreads = true;
resultN = NArray.CreateLike(a);
Console.WriteLine("Deferred threaded");
Timeit(
() =>
{
NArray.Evaluate(vectorOptions, () =>
{
return 3 * NMath.Log(NMath.Exp(a) * NMath.Exp(b));
});
});
Console.WriteLine(CheckitString(result, (resultN.Storage as ManagedStorage<double>).Array));
Console.WriteLine(Environment.NewLine);
resultN = NArray.CreateLike(a);
vectorOptions.MultipleThreads = false;
Console.WriteLine("Deferred not threaded");
Timeit(
() =>
{
NArray.Evaluate(vectorOptions, () =>
{
return 3 * NMath.Log(NMath.Exp(a) * NMath.Exp(b));
});
});
Console.WriteLine(CheckitString(result, (resultN.Storage as ManagedStorage<double>).Array));
Console.WriteLine(Environment.NewLine);
Console.WriteLine("Immediate");
Timeit(
() =>
{
resultN.Assign(3 * NMath.Log(NMath.Exp(a) * NMath.Exp(b)));
});
Console.WriteLine(CheckitString(result, (resultN.Storage as ManagedStorage<double>).Array));
Console.WriteLine(Environment.NewLine);
Console.WriteLine("Hit any key");
Console.ReadKey();
}
public void SimpleSpeedTest()
{
var factory = new NArrayFactory(StorageLocation.Host);
IntelMathKernelLibrary.SetAccuracyMode(VMLAccuracy.LowAccuracy);
int length = 1024 * 5;
var a = factory.CreateFromEnumerable(Enumerable.Range(0, length).Select(i => (double)i / length));
var a2 = (a.Storage as VectorAccelerator.NArrayStorage.ManagedStorage <double>).Array;
var b = factory.CreateFromEnumerable(Enumerable.Range(3, length).Select(i => (double)i / length));
var b2 = (b.Storage as VectorAccelerator.NArrayStorage.ManagedStorage <double>).Array;
double[] result = null;
NArray resultN = null;
Console.WriteLine("Allocation");
Timeit(
() =>
{
result = new double[length];
});
Console.WriteLine(Environment.NewLine);
result = new double[length];
Console.WriteLine("Managed optimal");
Timeit(
() =>
{
for (int i = 0; i < result.Length; ++i)
//Parallel.For(0, result.Length, (i) =>
{
result[i] = 3 * Math.Log(Math.Exp(a2[i]) * Math.Exp(b2[i]));
}
//);
});
Console.WriteLine(Environment.NewLine);
var vectorOptions = new VectorAccelerator.DeferredExecution.VectorExecutionOptions();
vectorOptions.MultipleThreads = true;
resultN = NArray.CreateLike(a);
Console.WriteLine("Deferred threaded");
Timeit(
() =>
{
NArray.Evaluate(vectorOptions, () =>
{
return(3 * NMath.Log(NMath.Exp(a) * NMath.Exp(b)));
});
});
Console.WriteLine(CheckitString(result, (resultN.Storage as ManagedStorage <double>).Array));
Console.WriteLine(Environment.NewLine);
resultN = NArray.CreateLike(a);
vectorOptions.MultipleThreads = false;
Console.WriteLine("Deferred not threaded");
Timeit(
() =>
{
NArray.Evaluate(vectorOptions, () =>
{
return(3 * NMath.Log(NMath.Exp(a) * NMath.Exp(b)));
});
});
Console.WriteLine(CheckitString(result, (resultN.Storage as ManagedStorage <double>).Array));
Console.WriteLine(Environment.NewLine);
Console.WriteLine("Immediate");
Timeit(
() =>
{
resultN.Assign(3 * NMath.Log(NMath.Exp(a) * NMath.Exp(b)));
});
Console.WriteLine(CheckitString(result, (resultN.Storage as ManagedStorage <double>).Array));
Console.WriteLine(Environment.NewLine);
Console.WriteLine("Hit any key");
Console.ReadKey();
}
