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Declarative Machine Learning
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
package org.apache.sysml.runtime.controlprogram.parfor.opt;
import java.util.ArrayList;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.sysml.lops.LopProperties.ExecType;
import org.apache.sysml.runtime.DMLRuntimeException;
import org.apache.sysml.runtime.controlprogram.parfor.opt.OptNode.ParamType;
import org.apache.sysml.runtime.controlprogram.parfor.opt.PerfTestTool.TestMeasure;
/**
* Base class for all potential cost estimators
*
* TODO account for shared read-only matrices when computing aggregated stats
*
*/
public abstract class CostEstimator
{
protected static final Log LOG = LogFactory.getLog(CostEstimator.class.getName());
//default parameters
public static final double DEFAULT_EST_PARALLELISM = 1.0; //default degree of parallelism: serial
public static final long FACTOR_NUM_ITERATIONS = 10; //default problem size
public static final double DEFAULT_TIME_ESTIMATE = 5; //default execution time: 5ms
public static final double DEFAULT_MEM_ESTIMATE_CP = 1024; //default memory consumption: 1KB
public static final double DEFAULT_MEM_ESTIMATE_MR = 10*1024*1024; //default memory consumption: 20MB
/**
* Main leaf node estimation method - to be overwritten by specific cost estimators
*
* @param measure
* @param node
* @return
* @throws DMLRuntimeException
*/
public abstract double getLeafNodeEstimate( TestMeasure measure, OptNode node )
throws DMLRuntimeException;
/**
* Main leaf node estimation method - to be overwritten by specific cost estimators
*
* @param measure
* @param node
* @param et forced execution type for leaf node
* @return
* @throws DMLRuntimeException
*/
public abstract double getLeafNodeEstimate( TestMeasure measure, OptNode node, ExecType et )
throws DMLRuntimeException;
/////////
//methods invariant to concrete estimator
///
/**
* Main estimation method.
*
* @param measure
* @param node
* @return
* @throws DMLRuntimeException
*/
public double getEstimate( TestMeasure measure, OptNode node )
throws DMLRuntimeException
{
return getEstimate(measure, node, null);
}
/**
* Main estimation method.
*
* @param measure
* @param node
* @return
* @throws DMLRuntimeException
*/
public double getEstimate( TestMeasure measure, OptNode node, ExecType et )
throws DMLRuntimeException
{
double val = -1;
if( node.isLeaf() )
{
if( et != null )
val = getLeafNodeEstimate(measure, node, et); //forced type
else
val = getLeafNodeEstimate(measure, node); //default
}
else
{
//aggreagtion methods for different program block types and measure types
//TODO EXEC TIME requires reconsideration of for/parfor/if predicates
//TODO MEMORY requires reconsideration of parfor -> potential overestimation, but safe
String tmp = null;
double N = -1;
switch ( measure )
{
case EXEC_TIME:
switch( node.getNodeType() )
{
case GENERIC:
case FUNCCALL:
val = getSumEstimate(measure, node.getChilds(), et);
break;
case IF:
if( node.getChilds().size()==2 )
val = getWeightedEstimate(measure, node.getChilds(), et);
else
val = getMaxEstimate(measure, node.getChilds(), et);
break;
case WHILE:
val = FACTOR_NUM_ITERATIONS * getSumEstimate(measure, node.getChilds(), et);
break;
case FOR:
tmp = node.getParam(ParamType.NUM_ITERATIONS);
N = (tmp!=null) ? (double)Long.parseLong(tmp) : FACTOR_NUM_ITERATIONS;
val = N * getSumEstimate(measure, node.getChilds(), et);
break;
case PARFOR:
tmp = node.getParam(ParamType.NUM_ITERATIONS);
N = (tmp!=null) ? (double)Long.parseLong(tmp) : FACTOR_NUM_ITERATIONS;
val = N * getSumEstimate(measure, node.getChilds(), et) / node.getK();
break;
default:
//do nothing
}
break;
case MEMORY_USAGE:
switch( node.getNodeType() )
{
case GENERIC:
case FUNCCALL:
case IF:
case WHILE:
case FOR:
val = getMaxEstimate(measure, node.getChilds(), et);
break;
case PARFOR:
if( node.getExecType() == OptNode.ExecType.MR )
val = getMaxEstimate(measure, node.getChilds(), et); //executed in different JVMs
else if ( node.getExecType() == OptNode.ExecType.CP )
val = getMaxEstimate(measure, node.getChilds(), et) * node.getK(); //everything executed within 1 JVM
break;
default:
//do nothing
}
break;
}
}
return val;
}
/**
*
* @param plan
* @param n
* @return
*/
public double computeLocalParBound(OptTree plan, OptNode n)
{
return Math.floor(rComputeLocalValueBound(plan.getRoot(), n, plan.getCK()));
}
/**
*
* @param plan
* @param n
* @return
*/
public double computeLocalMemoryBound(OptTree plan, OptNode n)
{
return rComputeLocalValueBound(plan.getRoot(), n, plan.getCM());
}
/**
*
* @param pn
* @return
*/
public double getMinMemoryUsage(OptNode pn)
{
// TODO implement for DP enum optimizer
throw new RuntimeException("Not implemented yet.");
}
/**
*
* @param measure
* @return
*/
protected double getDefaultEstimate(TestMeasure measure)
{
double val = -1;
switch( measure )
{
case EXEC_TIME: val = DEFAULT_TIME_ESTIMATE; break;
case MEMORY_USAGE: val = DEFAULT_MEM_ESTIMATE_CP; break;
}
return val;
}
/**
*
* @param measure
* @param nodes
* @return
* @throws DMLRuntimeException
*/
protected double getMaxEstimate( TestMeasure measure, ArrayList nodes, ExecType et )
throws DMLRuntimeException
{
double max = Double.MIN_VALUE; //smallest positive value
for( OptNode n : nodes )
{
double tmp = getEstimate( measure, n, et );
if( tmp > max )
max = tmp;
}
return max;
}
/**
*
* @param measure
* @param nodes
* @return
* @throws DMLRuntimeException
*/
protected double getSumEstimate( TestMeasure measure, ArrayList nodes, ExecType et )
throws DMLRuntimeException
{
double sum = 0;
for( OptNode n : nodes )
sum += getEstimate( measure, n, et );
return sum;
}
/**
*
* @param measure
* @param nodes
* @return
* @throws DMLRuntimeException
*/
protected double getWeightedEstimate( TestMeasure measure, ArrayList nodes, ExecType et )
throws DMLRuntimeException
{
double ret = 0;
int len = nodes.size();
for( OptNode n : nodes )
ret += getEstimate( measure, n, et );
ret /= len; //weighting
return ret;
}
/**
*
* @param current
* @param node
* @param currentVal
* @return
*/
protected double rComputeLocalValueBound( OptNode current, OptNode node, double currentVal )
{
if( current == node ) //found node
return currentVal;
else if( current.isLeaf() ) //node not here
return -1;
else
{
switch( current.getNodeType() )
{
case GENERIC:
case FUNCCALL:
case IF:
case WHILE:
case FOR:
for( OptNode c : current.getChilds() )
{
double lval = rComputeLocalValueBound(c, node, currentVal);
if( lval > 0 )
return lval;
}
break;
case PARFOR:
for( OptNode c : current.getChilds() )
{
double lval = rComputeLocalValueBound(c, node, currentVal/current.getK());
if( lval > 0 )
return lval;
}
break;
default:
//do nothing
}
}
return -1;
}
}