Abstract

Applications designed to execute on "computational grids" frequently require the simultaneous co-allocation of multiple resources in order to meet performance requirements. For example, several computers and network elements may be required in order to achieve real-time reconstruction of experimental data, while a large numerical simulation may require simultaneous access to multiple supercomputers. Motivated by these concerns, we have developed a general resource management architecture for Grid environments, in which resource co-allocation is an integral component. In this paper, we examine the coallocation problem in detail and present mechanisms that allow an application to guide resource selection during the co-allocation process; these mechanisms address issues relating to the allocation, monitoring, control, and configuration of distributed computations. We describe the implementation of co-allocators based on these mechanisms and present the results of microbenchmark studies and largescale application experiments that provide insights into the costs and practical utility of our techniques.

Citations