1. 1 Artificial Evolution: From Clusters to GRID Erol Şahin Cevat Şener Dept. of Computer Engineering Middle East Technical University Ankara

2. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 2 Darwinian Evolution A population consists of a variety of individuals. The traits of individuals are determined by their genomes. Fitter individuals tend to produce more-than-average off-springs. Off-springs are generated by a recombination of the genomes of the fitter individuals.

3. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 3 Artificial Evolution Generate a population of solutions. Evaluate the quality of each solution using a pre-defined “fitness function”. Use the fitter solutions to generate more- than-average new solutions. New solutions generated by a recombination of fitter solutions.

4. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 4 EVOLUTION Environment Individual Fitness PROBLEM SOLVING Problem Candidate Solution Quality Quality  chance for seeding new solutions Fitness  chances for survival and reproduction The metaphor Slide taken from Eiben and Smith’s presentation.

5. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 5 Evolutionary robotics Challenge: How to design a controller that would make the robot to perform a desired task? –Manual controller design is often difficult/impossible –Realistic simulators are used to evaluate different controller alternatives.

6. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 6 Evolutionary robotics 010101 100111... Sensor data Actuator outputs Convert to controller parameters Use the controller in robots Controller Chromosome

7. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 7 Evolving controllers........... Generation n Chrom.1: 0101011001... Chrom.2: 1100110111............ Generation n+1 Select Reproduce Mutate........... Chrom.1: 1010001110... Chrom.2: 0011110101............ Population n Population n+1

8. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 8 Physics Based Simulation Pros –Faster and more reliable than experimentation with real robots –Realistic Cons –High processing demand!

9. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 9 Single Machine Limitations Computation required: –Solving Ordinary Differential Equations –Increasing complexity with more collisions Time estimates for single computer: –Order of minutes for a single evaluation –For 100 chromosomes and 100 generations Total time > a week on a single machine

10. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 10 Parallel Evolution System (PES) on a Cluster

11. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 11 PES Architecture Server: Artificial Evolution Clients: Fitness evaluation PES-C Client Application PES-S Server Application

12. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 12 PES Communication Model PES Network Adapter PVM Host PES-C PES Network Adapter PVM Host PES-S

13. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 13 PES-S Architecture Server Application Artificial Evolution Task Manager PES-S Configuration Manager Task generator Best solutions

14. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 14 PES-C Architecture PES-C Client Application Simulator Fitness Evaluator Task Fitness

15. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 15 Processor Load Balancing Dynamic simulation Varying number of collisions Varying task complexity Varying processor load Diamonds and Hexagons: tasks Solid lines: Start of new generation

16. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 16 Fault Tolerance Processor 2 fails Detected at ping at 15 th sec Task restart at 19 th sec Red lines: Ping Blue lines: Generation Numbers: Task index

17. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 17 Efficiency & Speedup

18. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 18 Generation Gap for 128 Processors

19. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 19 Implementing PES on a Grid Two alternatives so far: 1.Porting PES as a whole from Clusters to Grid 2.Submitting only the clients onto Grid

20. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 20 Porting the whole PES 16 pvm PES-S,PES-C,PES-C,...,PES-C PES-S PES-C pvmd... Grid Engine

21. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 21 Porting the whole PES Advantage –Easy implementation Disadvantage –Requires that 16 nodes become available at the same time to start running

22. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 22 Only Clients JobArray: 1:15 PES-C PES-S PES-C... Grid Engine PES-C Task Submission Results

23. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 23 Only Clients Disadvantage –Communication and synchronization setup between PES-S and Grid Engine is not straightforward Advantage –Performance

24. Ulusal GRID Çalıştayı, 21-22 Eylül 2005, Ankara 24 Questions/Comments?