The workflow framework for metaheuristic search on grid environment
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The Workflow Framework for Metaheuristic Search on Grid Environment. Dang-Khoa Tran Van Hoai Tran Faculty of Computer Science and Engineering HCMC University of Technology. Metaheuristic. Combinatorial optimization problems are often NP-hard, cannot solve in reasonable time.

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The workflow framework for metaheuristic search on grid environment

The Workflow Framework for Metaheuristic Search on Grid Environment

Dang-Khoa Tran

Van Hoai Tran

Faculty of Computer Science and Engineering

HCMC University of Technology


Metaheuristic
Metaheuristic

  • Combinatorial optimization problems are often NP-hard, cannot solve in reasonable time.

  • Meta-heuristic is not like the exact methods, it can find reasonable solutions in acceptable time.

HPSC 2009


Metaheuristic1
Metaheuristic

  • Improving the solutions by expanding the exploration space and with various strategies

    • Take more time

    • … or required more computing resources

  • Our approach: using Grid Computing to solve the metaheuristic problem.

HPSC 2009


Content
Content

  • Meta-heuristic and Grid Computing

  • Design goals

  • The framework designs

  • Experiments and results

HPSC 2009


Grid computing
Grid computing

  • Grid Computing is the parallel and distributed system that enables the sharing and using resources easily.

  • Grid programming paradigm: using Parallel Object C++ (POP-C++) for application development.

    • Similar to C++ with a few keyword.

    • The objects are automatically created and executed on Grid.

HPSC 2009


Some challenges
Some challenges

  • User is usually not familiar with Grid programming model.

  • Application testing and debugging on Grid is difficult.

  • Make use of Grid computing by executing many search algorithm concurrently.

HPSC 2009


Design goals for the framework
Design Goals for the Framework

  • Provide workflow model to solve the problems

  • Easy to develop applications

    • Using OO programming

    • Hide the Grid programming model from user

  • Test and debug the applications

  • Deploy and execute on Grid environment easily

  • Running efficiency

HPSC 2009


Library architecture
Library Architecture

Applications

Parallel Metaheuristic Library

Search Algorithms

Workflow Engine

POP-C++ Runtime

Computing Resources

(Workstations / Clusters / Grid)

HPSC 2009


Easy to use
Easy to Use

  • Using the search algorithms

    • Inherits from predefined interfaces

    • Implements the abstract methods

  • Using workflow

    • Create dependency graph

    • The workflow engine will handles the execution

HPSC 2009


Easy to use example
Easy to Use – Example

// Define search algorithm

myTwoOpttwo_opt(graph);

myTwoOptNexttwo_opt_next(graph);

edaBestImprSelectmoveSelect;

edaHChcSearch( &two_opt, &two_opt_next, &moveSelect);

/* Define more search algorithms... */

// Define workflow control: Using Parallel workflow

edaParWrapperControlsfControl;

// Create dependency graph

inthcId = sfControl.insertVertex( &hcSearch );

sfControl.insertEdge( hcId, saId );

// Do search

sfControl.search(route)

HPSC 2009


Sample workflow
Sample workflow

Initial solution

TS

SA

HC

SA

HC

S

SA

TS

HPSC 2009


Easy to deploy
Easy to Deploy

HPSC 2009


Easy to test and debug
Easy to Test and Debug

  • Testing and Debugging

    • Using the sequential workflow

    • Test and debug like normal applications

HPSC 2009



The traveling salesman problem1
The Traveling Salesman Problem

  • Workflow design for testing

SA

HC

TS

HC

HC

HC

SA

HC

Output: path

Input: graph

TS

HC

...

HPSC 2009



Logic circuit optimization
Logic Circuit Optimization

  • Size optimization

  • Delay optimization

  • Energy optimization

HPSC 2009


Logic circuit optimization1
Logic Circuit Optimization

  • Workflow design

TS

SA

TS

SA

TS

SA

TS

SA

HC

HC

TS

SA

TS

SA

HPSC 2009


Logic circuit optimization2
Logic Circuit Optimization

  • Sample circuit: IWLS93

  • Sequential execution (1 branch of the workflow)

  • Literal optimization

HPSC 2009


Logic circuit optimization3
Logic Circuit Optimization

  • Execute concurrently on Grid

  • Execute a few times each (average results)

  • Literal optimization

HPSC 2009


Future work and conclusion
Future Work and Conclusion

  • Support the evolution-based heuristic.

  • Provide more sophisticated workflow such as loop, branching and parallel branches.

HPSC 2009



Question
Question!?

HPSC 2009


PCB442

HPSC 2009





ALI535

HPSC 2009





EIL101

HPSC 2009





PR1002

HPSC 2009





Literal optimization result
Literal Optimization Result

Optimize

count.blif – IWLS93

HPSC 2009


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