Chapter 11: Fault-Tolerant and Adaptive Programs with PVM

Chapter 11: Fault-Tolerant and Adaptive Programs with PVM

Overview

Al Geist and Jim Kohl

A number of factors must be considered when you are developing applications for Beowulf clusters. In the preceding chapters the basic methods of message passing were illustrated so that you could create your own parallel programs. This chapter describes the issues and common methods for making parallel programs that are fault tolerant and adaptive.

Fault tolerance is the ability of an application to continue to run or make progress even if a hardware or software problem causes a node in the cluster to fail. It is also the ability to tolerate failures within the application itself. For example, one task inside a parallel application may get an error and abort, but the rest of the tasks are able to carry on the calculation. Because Beowulf clusters are built from commodity components that are designed for the desktop rather than heavy-duty computing, failures of components inside a cluster are higher than in a more expensive multiprocessor system that has an integrated RAS (Reliability, Availability, Serviceability) system.

While fault-tolerant programs can be thought of as adaptive, the term "adaptive programs" is used here more generally to mean parallel (or serial) programs that dynamically change their characteristics to better match the application's needs and the available resources. Examples include an application that adapts by adding or releasing nodes of the cluster according to its present computational needs and an application that creates and kills tasks based on what the computation needs.

In later chapters you will learn about Condor and other resource management tools that automatically provide some measure of fault tolerance and adaptability to jobs submitted to them. This chapter teaches the basics of how to write such tools yourself.

PVM is based on a dynamic computing model in which cluster nodes can be added and deleted from the computation on the fly and parallel tasks can be spawned or killed during the computation. PVM doesn't have nearly as rich a set of message-passing features as MPI; but, being a virtual machine model, PVM has a number of features that make it attractive for creating dynamic parallel programs. For this reason, PVM will be used to illustrate the concepts of fault tolerance and adaptability in this chapter.




Part III: Managing Clusters