Parallelized Evolution System (PES)

This system is being developed in conjunction with IRIDIA within our collaboration on the Swarm-bots project. The system  parallelizes the  execution of  evolutionary methods over multiple computers connected via a network. PES is based upon PVM, a popular parallel programming library.

Features:

• Simple usage
• Load balancing
• Fundamental genetic algorithm facilities
• improved fault tolerance via built-in ping mechanism
• Multi platform support and interoperability

Architecture:

PES runs GA centrally on the server but distributes function evaluations to the clients.  This scheme is more effective when the fitness evaluations dominate the execution time of program. Following figure demonstrates the architecture of a PES application.

1. a server component, named PES-S. This component is used for server application:
   
• Fundamental GA functionality: crossover/mutation and selection mechanisms for binary strings and built-in neural network class. These mechanisms can be replaced with custom ones for specific applications.
• Task management: sending tasks. A task is defined as data required to evaluate a fitness.  This can range from a simple bit string to a neural network controller together with definition of world it operates.  PES-S provides functions to serialize and deserialize tasks to send to clients.  PES also handles simple load balancing so that the faster clients receive more work whereas slower clients receive less. 
• Result management: Receiving tasks from clients and matching results with tasks.
• Ping mechanism: This mechanism keeps track of active clients.  PES-S functions send and receive ping packets to clients while evaluating fitness functions. This allows not responding clients to be detected and dropped. With this mechanism allows server to keep a stable rate of execution and also allows more fault tolerance. 
• Configuration manager: this class encapsulates options for PES. These include execution environment specific options and configurations. PES-S can load these options from a predefined file.  This reduces requirement for building for different applications.
  
2. Client component, named PES-C. This components is used for client application:
   
• Task Management: receiving tasks from server. 
• Ping mechanism: updating server about status of current task.
• Result management: sending result of execution to server.
  

Server uses PES-S functionality to distribute tasks and collect results. Server implementer need not worry about details on how tasks distributed or how results are collected. A single library call handles this task. So server program looks exactly like a serial program, free of inter-process communication. 

Client on the other hand uses PES-C to receive tasks and send results. Only part that requires special care in client programming is checking messages (a single function call from PES) so that pings are replied appropriately and new tasks are received.