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High performance arbitrary precision arithmetic library
package org.apfloat.internal;
import org.apfloat.ApfloatContext;
import org.apfloat.ApfloatRuntimeException;
import org.apfloat.spi.ConvolutionStrategy;
import org.apfloat.spi.DataStorageBuilder;
import org.apfloat.spi.DataStorage;
/**
* Medium-length convolution strategy.
* Performs a simple O(n2) multiplication when the size of one operand is relatively short.
*
* @version 1.8.0
* @author Mikko Tommila
*/
public class FloatMediumConvolutionStrategy
extends FloatBaseMath
implements ConvolutionStrategy
{
// Implementation notes:
// - Assumes that the operands have been already truncated to match resultSize (the resultSize argument is ignored)
// - This class probably shouldn't be converted to a single class using generics because there is some performance impact
/**
* Creates a convolution strategy using the specified radix.
*
* @param radix The radix that will be used.
*/
public FloatMediumConvolutionStrategy(int radix)
{
super(radix);
}
public DataStorage convolute(DataStorage x, DataStorage y, long resultSize)
throws ApfloatRuntimeException
{
DataStorage shortStorage, longStorage;
if (x.getSize() > y.getSize())
{
shortStorage = y;
longStorage = x;
}
else
{
shortStorage = x;
longStorage = y;
}
long shortSize = shortStorage.getSize(),
longSize = longStorage.getSize(),
size = shortSize + longSize;
if (shortSize > Integer.MAX_VALUE)
{
throw new ApfloatInternalException("Too long shorter number, size = " + shortSize);
}
final int bufferSize = (int) shortSize;
ApfloatContext ctx = ApfloatContext.getContext();
DataStorageBuilder dataStorageBuilder = ctx.getBuilderFactory().getDataStorageBuilder();
DataStorage resultStorage = dataStorageBuilder.createDataStorage(size * 4);
resultStorage.setSize(size);
DataStorage.Iterator src = longStorage.iterator(DataStorage.READ, longSize, 0),
dst = resultStorage.iterator(DataStorage.WRITE, size, 0),
tmpDst = new DataStorage.Iterator() // Cyclic iterator
{
public void next()
{
this.position++;
this.position = (this.position == bufferSize ? 0 : this.position);
}
public float getFloat()
{
return this.buffer[this.position];
}
public void setFloat(float value)
{
this.buffer[this.position] = value;
}
private static final long serialVersionUID = 1L;
private float[] buffer = new float[bufferSize];
private int position = 0;
};
for (long i = 0; i < longSize; i++)
{
DataStorage.Iterator tmpSrc = shortStorage.iterator(DataStorage.READ, shortSize, 0); // Sub-optimal: this could be cyclic also
float factor = src.getFloat(), // Get one word of source data
carry = baseMultiplyAdd(tmpSrc, tmpDst, factor, 0, tmpDst, shortSize),
result = tmpDst.getFloat(); // Least significant word of the result
dst.setFloat(result); // Store one word of result
tmpDst.setFloat(carry); // Set carry from calculation as new last word in cyclic buffer
tmpDst.next(); // Cycle buffer; current first word becomes last
src.next();
dst.next();
}
// Exhaust last words from temporary cyclic buffer and store them to result data
for (int i = 0; i < bufferSize; i++)
{
float result = tmpDst.getFloat();
dst.setFloat(result);
tmpDst.next();
dst.next();
}
return resultStorage;
}
private static final long serialVersionUID = -6697305140738370764L;
}
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