public static IList<NArray> Evaluate(Func<NArray> function, IList<NArray> independentVariables, StringBuilder expressionsOut = null,
Aggregator aggregator = Aggregator.ElementwiseAdd, IList<NArray> existingStorage = null, VectorExecutionOptions vectorOptions = null)
{
if (existingStorage != null && existingStorage.Count != independentVariables.Count + 1)
throw new ArgumentException(string.Format("storage provided does not match requirement for 1 result and {0} derivatives",
independentVariables.Count));
var timer = new ExecutionTimer();
timer.Start();
NArray[] outputs = new NArray[independentVariables.Count + 1];
var context = new DeferredExecutionContext(new VectorExecutionOptions(), independentVariables);
NArray dependentVariable;
try
{
// execute function as deferred operations and obtain reference to the dependentVariable
dependentVariable = function();
}
finally
{
context.Finish();
}
timer.MarkFunctionComplete();
for (int i = 0; i < outputs.Length; ++i)
{
// if new storage is required, we create scalars in the first instance
outputs[i] = (existingStorage == null) ? NArray.CreateScalar(0) : existingStorage[i];
}
context._executor.Evaluate(context._options, outputs, dependentVariable, independentVariables,
timer, expressionsOut, aggregator);
//Console.WriteLine(timer.Report());
return outputs;
}
private DeferredExecutionContext(VectorExecutionOptions options, IList<NArray> independentVarables)
{
_executor = new DeferringExecutor(independentVarables);
_previousExecutor = ExecutionContext.Executor;
_options = options;
ExecutionContext.Executor = _executor;
}
private DeferredExecutionContext(VectorExecutionOptions options, IList <NArray> independentVarables)
{
_executor = new DeferringExecutor(independentVarables);
_previousExecutor = ExecutionContext.Executor;
_options = options;
ExecutionContext.Executor = _executor;
}
public static void Execute(DeferringExecutor executor,
LinearAlgebraProvider provider, VectorExecutionOptions vectorOptions)
{
//Console.WriteLine(executor.DebugString());
int chunksLength = 1000;
var arrayPoolStack = ExecutionContext.ArrayPool.GetStack(chunksLength);
while (arrayPoolStack.Count < 10)
{
arrayPoolStack.Push(new double[chunksLength]);
}
int length = executor.VectorsLength;
int chunkCount = length / chunksLength;
if (length % chunksLength != 0)
{
chunkCount++;
}
//AssignNArrayStorage(executor.LocalVariables.OfType<NArray<double>>(), chunkCount, chunksLength);
// and integers too?
var options = new ParallelOptions();
if (!vectorOptions.MultipleThreads)
{
options.MaxDegreeOfParallelism = 1;
}
//for (int i = 0; i < chunkCount; i++)
var operations = Simplify(executor, provider);
Parallel.For(0, chunkCount, options, (i) =>
{
int startIndex = i * chunksLength;
List <double[]> temporaryArrays = new List <double[]>();
int vectorLength = Math.Min(chunksLength, length - startIndex);
foreach (var operation in operations)
{
if (operation is NArrayOperation <double> )
{
ExecuteSingleVectorOperation <double>(operation as NArrayOperation <double>,
arrayPoolStack, temporaryArrays,
vectorLength,
i, startIndex);
}
}
foreach (var array in temporaryArrays)
{
arrayPoolStack.Push(array);
}
});
//};
}
public void OptionPricingTest()
{
var location = StorageLocation.Host;
var a = new NArray(location, Enumerable.Range(0, 10).Select(i => (double)i).ToArray());
var b = new NArray(location, Enumerable.Range(0, 10).Select(i => (double)i * 2).ToArray());
var c = 5 - b;
var check = c.First();
IntelMathKernelLibrary.SetAccuracyMode(VMLAccuracy.LowAccuracy);
IntelMathKernelLibrary.SetSequential();
using (var randomStream = new RandomNumberStream(location, RandomNumberGeneratorType.MRG32K3A, 111))
{
var normalDistribution = new Normal(randomStream, 0, 1);
var vectorOptions = new VectorExecutionOptions() { MultipleThreads = true };
var watch = new Stopwatch();
watch.Start();
var optionPrices = Value(normalDistribution);
Console.WriteLine(String.Format("Start-up: {0}ms", watch.ElapsedMilliseconds));
randomStream.Reset();
watch.Restart();
optionPrices = Value(normalDistribution);
Console.WriteLine(String.Format("Threaded, deferred 1: {0}ms", watch.ElapsedMilliseconds));
randomStream.Reset();
watch.Restart();
var optionPricesDeferred = Value(normalDistribution);
Console.WriteLine(String.Format("Threaded, deferred 2: {0}ms", watch.ElapsedMilliseconds)); watch.Restart();
Console.WriteLine(TestHelpers.AgreesAbsoluteString(optionPrices, optionPricesDeferred));
}
}
public void TestBlackScholes()
{
var location = StorageLocation.Host;
using (var randomStream = new RandomNumberStream(location, RandomNumberGeneratorType.MRG32K3A, 111))
{
var normalDistribution = new Normal(randomStream, 0, 1);
double deltaT = 1;
double r = 0.1;
double vol = 0.3;
var options = new ParallelOptions();
options.MaxDegreeOfParallelism = 1;
var variates = NArray.CreateRandom(5000, normalDistribution);
NArray optionPrices = NArray.CreateLike(variates);
var watch = new Stopwatch(); watch.Start();
Parallel.For(0, 1000, options, (i) =>
{
optionPrices = NArray.CreateLike(variates);
var logStockPrice = Math.Log(100)
+ variates * Math.Sqrt(deltaT) * vol + (r - 0.5 * vol * vol) * deltaT;
var stockPrices = NMath.Exp(logStockPrice);
optionPrices.Assign(Finance.BlackScholes(-1, stockPrices, 90, 0.2, 1));
});
Console.WriteLine("Baseline sequential");
Console.WriteLine(watch.ElapsedMilliseconds); watch.Restart();
Parallel.For(0, 1000, (i) =>
{
optionPrices = NArray.CreateLike(variates);
var logStockPrice = Math.Log(100)
+ variates * Math.Sqrt(deltaT) * vol + (r - 0.5 * vol * vol) * deltaT;
var stockPrices = NMath.Exp(logStockPrice);
optionPrices.Assign(Finance.BlackScholes(-1, stockPrices, 90, 0.2, 1));
});
Console.WriteLine("Baseline threaded");
Console.WriteLine(watch.ElapsedMilliseconds);
NArray optionPrices2 = NArray.CreateLike(variates);
watch.Restart();
var vectorOptions = new DeferredExecution.VectorExecutionOptions() { MultipleThreads = true };
Parallel.For(0, 1000, options, (i) =>
{
optionPrices2 = NArray.CreateLike(variates);
NArray.Evaluate(optionPrices2, () =>
{
var logStockPrice = Math.Log(100)
+ variates * Math.Sqrt(deltaT) * vol + (r - 0.5 * vol * vol) * deltaT;
var stockPrices = NMath.Exp(logStockPrice);
return Finance.BlackScholes(-1, stockPrices, 90, 0.2, 1);
});
});
Console.WriteLine("Deferred sequential");
Console.WriteLine(watch.ElapsedMilliseconds);
Console.WriteLine(CheckitString((optionPrices.Storage as ManagedStorage<double>).Array, (optionPrices2.Storage as ManagedStorage<double>).Array));
watch.Restart();
Parallel.For(0, 1000, (i) =>
{
//optionPrices2 = NArray.CreateLike(variates);
optionPrices2 = NArray.Evaluate(() =>
{
var logStockPrice = Math.Log(100)
+ variates * Math.Sqrt(deltaT) * vol + (r - 0.5 * vol * vol) * deltaT;
var stockPrices = NMath.Exp(logStockPrice);
return Finance.BlackScholes(-1, stockPrices, 90, 0.2, 1);
});
});
Console.WriteLine("Deferred threaded");
Console.WriteLine(watch.ElapsedMilliseconds); watch.Restart();
Console.WriteLine(CheckitString((optionPrices.Storage as ManagedStorage<double>).Array, (optionPrices2.Storage as ManagedStorage<double>).Array));
}
}
public static IList <NArray> Evaluate(Func <NArray> function, IList <NArray> independentVariables, StringBuilder expressionsOut = null,
Aggregator aggregator = Aggregator.ElementwiseAdd, IList <NArray> existingStorage = null, VectorExecutionOptions vectorOptions = null)
{
if (existingStorage != null && existingStorage.Count != independentVariables.Count + 1)
{
throw new ArgumentException(string.Format("storage provided does not match requirement for 1 result and {0} derivatives",
independentVariables.Count));
}
var timer = new ExecutionTimer();
timer.Start();
NArray[] outputs = new NArray[independentVariables.Count + 1];
var context = new DeferredExecutionContext(new VectorExecutionOptions(), independentVariables);
NArray dependentVariable;
try
{
// execute function as deferred operations and obtain reference to the dependentVariable
dependentVariable = function();
}
finally
{
context.Finish();
}
timer.MarkFunctionComplete();
for (int i = 0; i < outputs.Length; ++i)
{
// if new storage is required, we create scalars in the first instance
outputs[i] = (existingStorage == null) ? NArray.CreateScalar(0) : existingStorage[i];
}
context._executor.Evaluate(context._options, outputs, dependentVariable, independentVariables,
timer, expressionsOut, aggregator);
//Console.WriteLine(timer.Report());
return(outputs);
}
