Package org.apache.sysds.hops.estim

Class EstimatorSampleRa

java.lang.Object

org.apache.sysds.hops.estim.SparsityEstimator

org.apache.sysds.hops.estim.EstimatorSampleRa

public class EstimatorSampleRa
extends SparsityEstimator

This estimator implements an approach based on row/column sampling Rasmus Resen Amossen, Andrea Campagna, Rasmus Pagh: Better Size Estimation for Sparse Matrix Products. Algorithmica 69(3): 741-757 (2014) Credit: This code is based on the original implementation provided by the authors, modified to fit the SparsityEstimator API, support binary matrix products, avoid unnecessary file access, use Well1024a for seeding local RNGs, and generally improve performance.

Nested Class Summary

Nested classes/interfaces inherited from class org.apache.sysds.hops.estim.SparsityEstimator

SparsityEstimator.OpCode

Field Summary

Fields inherited from class org.apache.sysds.hops.estim.SparsityEstimator

MIN_PAR_THRESHOLD, MULTI_THREADED_BUILD, MULTI_THREADED_ESTIM

Constructor Summary

Constructors

Constructor	Description
EstimatorSampleRa()
EstimatorSampleRa(double sampleFrac)
EstimatorSampleRa(int runs, double sampleFrac, double eps, double delta, int k)

Method Summary

Modifier and Type	Method	Description
DataCharacteristics	estim(MMNode root)	Estimates the output sparsity of a DAG of matrix multiplications for the given operator graph of a single root node.
double	estim(MatrixBlock m, SparsityEstimator.OpCode op)	Estimates the output sparsity for a given unary operation.
double	estim(MatrixBlock m1, MatrixBlock m2)	Estimates the output sparsity for a single matrix multiplication.
double	estim(MatrixBlock m1, MatrixBlock m2, SparsityEstimator.OpCode op)	Estimates the output sparsity for a given binary operation.
double	h(int x, int y)
void	sortAndTruncate(ArrayList<Double> sketch)

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

EstimatorSampleRa

public EstimatorSampleRa()

EstimatorSampleRa

public EstimatorSampleRa(double sampleFrac)

EstimatorSampleRa

public EstimatorSampleRa(int runs,
                         double sampleFrac,
                         double eps,
                         double delta,
                         int k)

Method Detail

estim

public DataCharacteristics estim(MMNode root)

Description copied from class: SparsityEstimator

Estimates the output sparsity of a DAG of matrix multiplications for the given operator graph of a single root node.

Specified by:

estim in class SparsityEstimator

Parameters:

root - DAG root node

Returns:

output data characteristics

estim

public double estim(MatrixBlock m1,
                    MatrixBlock m2,
                    SparsityEstimator.OpCode op)

Description copied from class: SparsityEstimator

Estimates the output sparsity for a given binary operation.

Specified by:

estim in class SparsityEstimator

Parameters:

m1 - left-hand-side operand

m2 - right-hand-side operand

op - operator code

Returns:

sparsity

estim

public double estim(MatrixBlock m,
                    SparsityEstimator.OpCode op)

Description copied from class: SparsityEstimator

Estimates the output sparsity for a given unary operation.

Specified by:

estim in class SparsityEstimator

Parameters:

m - left-hand-side operand

op - operator code

Returns:

sparsity

estim

public double estim(MatrixBlock m1,
                    MatrixBlock m2)

Description copied from class: SparsityEstimator

Estimates the output sparsity for a single matrix multiplication.

Specified by:

estim in class SparsityEstimator

Parameters:

m1 - left-hand-side operand

m2 - right-hand-side operand

Returns:

sparsity

sortAndTruncate

public void sortAndTruncate(ArrayList<Double> sketch)

h

public double h(int x,
                int y)