Reducing memory allocations #6
Description
I played around with the ILinearSolver interface of the sparse-matrices branch. Here's an implemetation which comes with zero additional memory allocations (using a custom LU implementation):
class OptimizedLinearSolverForTesting : ILinearSolver
{
private ReusableLU lu;
private Vector<double> solution;
public OptimizedLinearSolverForTesting(int dimension)
{
this.lu = new ReusableLU(dimension);
this.solution = new DenseVector(dimension);
}
public void Update(DenseMatrix stiffness)
{
lu.Compute(stiffness);
}
public Vector<double> Solve(Vector<double> input)
{
lu.Solve(input.AsArray(), solution.AsArray());
return solution;
}
}It would be used like this:
[Fact]
public void SolveQuadraticFunctionSmallIncrements()
{
// ALLOCATE MEMORY
var reaction = new DenseVector(2);
var stiffness = new DenseMatrix(2, 2);
var solver = new OptimizedLinearSolverForTesting(2);
// ARRANGE
Vector<double> Reaction(Vector<double> u)
{
reaction[0] = u[0] * u[0] + 2 * u[1] * u[1];
reaction[1] = 2 * u[0] * u[0] + u[1] * u[1];
return reaction;
};
ILinearSolver Stiffness(Vector<double> u)
{
stiffness[0, 0] = 2 * u[0];
stiffness[0, 1] = 4 * u[1];
stiffness[1, 0] = 4 * u[0];
stiffness[1, 1] = 2 * u[1];
solver.Update(stiffness);
return solver;
}
DenseVector force = new DenseVector(2) { [0] = 3, [1] = 3 };
NonLinearSolver Solver = NonLinearSolver.Builder
.Solve(2, Reaction, Stiffness)
.Under(force)
.WithInitialConditions(0.1, DenseVector.Create(2, 0), DenseVector.Create(2, 1))
.UsingStandardNewtonRaphsonScheme(0.01)
.Build();
// ACT
List<LoadState> states = Solver.Broadcast().TakeWhile(x => x.Lambda <= 1).ToList();
// ASSERT
AssertSolutionsAreCorrect(Reaction, force, states);
}As already mentioned in #2 (comment), there are a couple of places in the NonLinearEquationsSolver code, where further optimization can be done (memory allocations in an iterative process should always be reduced as much as possible).
That's also a point where CSparse.NET has to be improved, if it should be used efficiently with this library (at the moment, matrix factors cannot be reused).