Collaborative Research: CSR-PSCE, SM: Adaptive Memory Management in Shared Environments

Canisius University Of Buffalo New York, Buffalo NY

Investigators

Abstract

Program performance is highly dependent on the amount of memory available to the program. In traditional computing systems, the memory working set of an application has a bounded size - providing more memory to an application improves performance until its working set is met. Once the working set is met, additional memory yields little or no benefit. However, in the presence of garbage collection (a technique for memory management where space that is unlikely to be reused by an application is automatically reclaimed), the relationship between program performance and memory allocation is more complex. Data is managed at three levels: the compiler manages data objects at the program level, the garbage collector manages the heap at the virtual machine level, and the virtual memory manager manages virtual memory at the operating system level. The middle layer plays a critical role. Increasing an application's heap size can reduce the frequency of garbage collections and improve performance, but too large a heap may trigger paging and degrade performance.