autopas::RandomSearch Class Reference

Randomly test a given number of configurations and select the fastest. More...

#include <RandomSearch.h>

Inheritance diagram for autopas::RandomSearch:

Collaboration diagram for autopas::RandomSearch:

Public Member Functions
	RandomSearch (size_t maxEvidence, unsigned long seed)
	Constructor.
TuningStrategyOption	getOptionType () const override
	Get this object's associated TuningStrategyOption type.
bool	reset (size_t, size_t tuningPhase, std::vector< Configuration > &configQueue, const autopas::EvidenceCollection &evidenceCollection) override
	Reset all internal parameters to the beginning of a new tuning phase.
bool	optimizeSuggestions (std::vector< Configuration > &configQueue, const EvidenceCollection &evidenceCollection) override
	Optimizes the queue of configurations to process.
void	addEvidence (const Configuration &configuration, const Evidence &evidence) override
	Notifies the strategy about empirically collected information for the given configuration.
Public Member Functions inherited from autopas::TuningStrategyInterface
virtual TuningStrategyOption	getOptionType () const =0
	Get this object's associated TuningStrategyOption type.
virtual void	addEvidence (const Configuration &configuration, const Evidence &evidence)
	Notifies the strategy about empirically collected information for the given configuration.
virtual bool	optimizeSuggestions (std::vector< Configuration > &configQueue, const EvidenceCollection &evidenceCollection)=0
	Optimizes the queue of configurations to process.
virtual bool	reset (size_t iteration, size_t tuningPhase, std::vector< Configuration > &configQueue, const autopas::EvidenceCollection &evidenceCollection)=0
	Reset all internal parameters to the beginning of a new tuning phase.
virtual bool	needsLiveInfo () const
	Returns whether this tuning strategy wants to get a LiveInfo object passed before a new tuning phase.
virtual void	receiveLiveInfo (const LiveInfo &info)
	Virtual method that subclasses can override to receive the LiveInfo object before a tuning phase if they return true in needsLiveInfo().
virtual void	rejectConfiguration (const Configuration &configuration, bool indefinitely)
	Notify the strategy about a configuration that is (currently) invalid and thus can potentially be dropped from some internal storage.
virtual bool	needsSmoothedHomogeneityAndMaxDensity () const
	Indicate whether the strategy needs smoothed values of homogeneity and max density.
virtual void	receiveSmoothedHomogeneityAndMaxDensity (double homogeneity, double maxDensity)
	Method to pass smoothed homogeneity and the maximal density to the tuning strategy.

Detailed Description

Randomly test a given number of configurations and select the fastest.

Constructor & Destructor Documentation

RandomSearch()

autopas::RandomSearch::RandomSearch ( size_t  maxEvidence, unsigned long  seed  )

explicit

Constructor.

Parameters

maxEvidence	Maximum number of evidence this strategy will collect. This number should be smaller than the available search space.
seed	Seed for the random number generator (should only be fixed for deterministic tests).

Member Function Documentation

addEvidence()

void autopas::RandomSearch::addEvidence ( const Configuration &  configuration, const Evidence &  evidence  )

overridevirtual

Notifies the strategy about empirically collected information for the given configuration.

All evidence is stored centrally in the AutoTuner and its EvidenceCollection is passed to the tuning strategies during optimization.

Implementing this function is only necessary if the tuning strategy processes evidence differently than EvidenceCollection.

Parameters

configuration	Configuration used to obtain the evidence.
evidence	Measurement and when it was taken.

Reimplemented from autopas::TuningStrategyInterface.

getOptionType()

autopas::TuningStrategyOption autopas::RandomSearch::getOptionType ( ) const

overridevirtual

Get this object's associated TuningStrategyOption type.

Returns

TuningStrategyOption

Implements autopas::TuningStrategyInterface.

optimizeSuggestions()

bool autopas::RandomSearch::optimizeSuggestions ( std::vector< Configuration > &  configQueue, const EvidenceCollection &  evidenceCollection  )

overridevirtual

Optimizes the queue of configurations to process.

This function is called once before each iteration in a tuning phase so all tuning strategies can give their input on which configuration to try next. This is done by reordering configQueue so that the next configuration to try is at the end (FIFO).

Parameters

configQueue	Queue of configurations to be tested. The tuning strategy should edit this queue.
evidenceCollection	All collected evidence until now.

Returns

boolean value to signal if the tuning strategy has intentionally wiped the config queue

Implements autopas::TuningStrategyInterface.

reset()

bool autopas::RandomSearch::reset ( size_t  iteration, size_t  tuningPhase, std::vector< Configuration > &  configQueue, const autopas::EvidenceCollection &  evidenceCollection  )

overridevirtual

Reset all internal parameters to the beginning of a new tuning phase.

This can also mean to reorder the configQueue to some initially expected state.

Parameters

iteration	Gives the current iteration to the tuning strategy.
tuningPhase	Gives the current tuning phase to the tuning strategy.
configQueue	Queue of configurations to be tested. The tuning strategy should edit this queue.
evidenceCollection	All collected evidence until now.

Returns

boolean value to signal if the tuning strategy has intentionally wiped the config queue

Implements autopas::TuningStrategyInterface.

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The documentation for this class was generated from the following files:

• autopas/tuning/tuningStrategy/RandomSearch.h
• autopas/tuning/tuningStrategy/RandomSearch.cpp