Dynamic Resource Provisioning in Grid Environments

Batch schedulers commonly used to manage access to parallel computing clusters are not typically configured to enable easy configuration of application-specific scheduling policies. In addition, their sophisticated scheduling algorithms can be relatively expensive to execute. Thus, for example, applications that require the rapid execution of many small tasks often do not perform well. It has been proposed that these problems be overcome by separating the two tasks of provisioning and scheduling. This paper focuses on resource provisioning, the various allocation and de-allocation policies, and how dynamic and adaptive provisioning can be in light of varying workloads. We couple the proposed dynamic resource provisioning (DRP) with an existing system, Falkon, which is used for the scheduling of tasks to the provisioned resources. We describe the DRP architecture and implementation, and present performance results for both microbenchmarks and applications. Microbenchmarks show that DRP can allocate resources on the order of 10s of seconds across multiple Grid sites and can reduce average queue wait times by up to 95 % (effectively yielding queue wait times within 3 % of ideal); furthermore, applications (executed by the Swift parallel programming system) reduce end-to-end run time of up to 90 % for large-scale astronomy and medical applications, relative to versions that execute tasks via separate scheduler submissions