Make c# matrix code faster
- by Wam
Hi all,
Working on some matrix code, I'm concerned of performance issues.
here's how it works : I've a IMatrix abstract class (with all matrices operations etc), implemented by a ColumnMatrix class.
abstract class IMatrix
{
public int Rows {get;set;}
public int Columns {get;set;}
public abstract float At(int row, int column);
}
class ColumnMatrix : IMatrix
{
private data[];
public override float At(int row, int column)
{
return data[row + columns * this.Rows];
}
}
This class is used a lot across my application, but I'm concerned with performance issues.
Testing only read for a 2000000x15 matrix against a jagged array of the same size, I get 1359ms for array access agains 9234ms for matrix access :
public void TestAccess()
{
int iterations = 10;
int rows = 2000000;
int columns = 15;
ColumnMatrix matrix = new ColumnMatrix(rows, columns);
for (int i = 0; i < rows; i++)
for (int j = 0; j < columns; j++)
matrix[i, j] = i + j;
float[][] equivalentArray = matrix.ToRowsArray();
TimeSpan totalMatrix = new TimeSpan(0);
TimeSpan totalArray = new TimeSpan(0);
float total = 0f;
for (int iteration = 0; iteration < iterations; iteration++)
{
total = 0f;
DateTime start = DateTime.Now;
for (int i = 0; i < rows; i++)
for (int j = 0; j < columns; j++)
total = matrix.At(i, j);
totalMatrix += (DateTime.Now - start);
total += 1f; //Ensure total is read at least once.
total = total > 0 ? 0f : 0f;
start = DateTime.Now;
for (int i = 0; i < rows; i++)
for (int j = 0; j < columns; j++)
total = equivalentArray[i][j];
totalArray += (DateTime.Now - start);
}
if (total < 0f)
logger.Info("Nothing here, just make sure we read total at least once.");
logger.InfoFormat("Average time for a {0}x{1} access, matrix : {2}ms", rows, columns, totalMatrix.TotalMilliseconds);
logger.InfoFormat("Average time for a {0}x{1} access, array : {2}ms", rows, columns, totalArray.TotalMilliseconds);
Assert.IsTrue(true);
}
So my question : how can I make this thing faster ? Is there any way I can make my ColumnMatrix.At faster ?
Cheers !
