public void Execute(VectorExecutionOptions options)
{
var codeBuilder = new CUDACodeBuilder();
var block = _builder.ToBlock();
codeBuilder.GenerateCode(block);
}
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));
}
}
/// <summary>
/// Here we execute the expression, but without attempting to compile it.
/// The performance gain comes only from reducing the amount of memory allocation required, not
/// from compiling an optimised kernel.
/// </summary>
/// <param name="block"></param>
/// <param name="provider"></param>
/// <param name="vectorOptions"></param>
public static void RunNonCompiling(BlockExpressionBuilder _builder,
LinearAlgebraProvider provider, VectorExecutionOptions vectorOptions,
NArray[] outputs, int[] outputsIndices, Aggregator aggregator, ExecutionTimer timer)
{
var block = _builder.ToBlock();
if (block.Operations.Count == 0)
{
return;
}
// we will cycle through arrays in order of increasing index
var getter = new OutputGetter <double>(outputs, outputsIndices);
int chunksLength = _builder.VectorLength; //5000;
var arrayPoolStack = ExecutionContext.ArrayPool.GetStack(chunksLength);
int length = (block.ArgumentParameters.First() as ReferencingVectorParameterExpression <double>)
.Array.Length;
int chunkCount = length / chunksLength;
if (length % chunksLength != 0)
{
chunkCount++;
}
List <NArray <double> >[] localsToFree; // the storage that can be freed up after each operation is complete
AssignNArrayStorage <double>(block, chunkCount, chunksLength, length, out localsToFree);
// for integer support, add here
var options = new ParallelOptions();
if (!vectorOptions.MultipleThreads)
{
options.MaxDegreeOfParallelism = 1;
}
timer.MarkExecutionTemporaryStorageAllocationComplete();
// can multi-thread here, but better to do so at higher level
//Parallel.For(0, chunkCount, options, (i) =>
for (int i = 0; i < chunkCount; ++i)
{
int startIndex = i * chunksLength;
int vectorLength = Math.Min(chunksLength, length - startIndex);
for (int j = 0; j < block.Operations.Count; ++j)
{
var operation = block.Operations[j];
if (operation.Type == typeof(NArray))
{
var newOperation = _builder.SimplifyOperation(operation); // deal with any expressions containing scalars that can be simplified
ExecuteSingleVectorOperation <double>(newOperation, provider,
arrayPoolStack, localsToFree[j],
getter, aggregator,
vectorLength,
i, startIndex, timer);
}
}
}
;
if (!arrayPoolStack.StackCountEqualsCreated)
{
throw new Exception("not all storage arrays created returned to stack");
}
}
public void Evaluate(VectorExecutionOptions options,
NArray[] outputs,
NArray dependentVariable, IList <NArray> independentVariables, ExecutionTimer timer, StringBuilder expressionsOut = null,
Aggregator aggregator = Aggregator.ElementwiseAdd)
{
if (aggregator != Aggregator.ElementwiseAdd)
{
throw new NotImplementedException();
}
var dependentVariableExpression = _builder.GetParameter <double>(dependentVariable);
var independentVariableExpressions = independentVariables.Select(v => _builder.GetParameter <double>(v)).ToArray();
// and important special case
// this can only occur if the dependent variable is a scalar that does not depend on any independent variables
if (dependentVariableExpression.Index == -1)
{
var scalarValue = (dependentVariableExpression as ReferencingVectorParameterExpression <double>).ScalarValue;
outputs[0].Add(scalarValue);
// all derivatives remains zero
return;
}
_builder.UpdateLocalsNumbering();
timer.MarkEvaluateSetupComplete();
// differentiate, extending the block as necessary
IList <Expression> derivativeExpressions;
AlgorithmicDifferentiator.Differentiate(_builder, out derivativeExpressions,
dependentVariableExpression, independentVariableExpressions);
timer.MarkDifferentationComplete();
// arrange output storage
var outputIndices = new int[1 + independentVariables.Count];
for (int i = 0; i < independentVariables.Count + 1; ++i)
{
var referencingExpression = (i > 0) ? derivativeExpressions[i - 1] as ReferencingVectorParameterExpression <double>
: dependentVariableExpression as ReferencingVectorParameterExpression <double>;
if (referencingExpression.IsScalar) // common case: constant derivative (especially zero)
{
outputs[i].Add(referencingExpression.ScalarValue);
outputIndices[i] = int.MaxValue;
// TODO if storage passed in, update here in case of non-zero constant?
}
else // not a scalar so we will need storage
{
outputIndices[i] = referencingExpression.Index;
if (outputs[i].IsScalar)
{
// we increase the storage, copying the scalar value
outputs[i] = new NArray(new VectorAccelerator.NArrayStorage.ManagedStorage <double>(_builder.VectorLength, 1, outputs[i].First()));
}
}
}
timer.MarkStorageSetupComplete();
// run
VectorBlockExpressionRunner.RunNonCompiling(_builder, Provider(StorageLocation.Host),
new VectorExecutionOptions(), outputs, outputIndices, aggregator, timer);
timer.MarkExecuteComplete();
if (expressionsOut != null)
{
var block = _builder.ToBlock();
expressionsOut.AppendLine("Result in expression "
+ dependentVariableExpression.ToString());
if (derivativeExpressions != null && derivativeExpressions.Any())
{
expressionsOut.AppendLine("Derivatives in expressions " + String.Join(", ",
derivativeExpressions.Select(e => e.ToString())));
}
foreach (var item in block.Operations)
{
var display = item.ToString();
expressionsOut.AppendLine(new string(display.ToArray()));
}
}
}
