A fast analysis for thread-local garbage collection with dynamic class loading

Jones, Richard E. and King, A.C. (2005) A fast analysis for thread-local garbage collection with dynamic class loading. In: Source Code Analysis and Manipulation, 2005, 30th September - 1st October 2005, Budapest, Hungary. (doi:https://doi.org/10.1109/SCAM.2005.1) (Full text available)

PDF (A Fast Analysis for Thread-Local Garbage Collection with Dynamic Class Laoding) - Author's Accepted Manuscript
Download (189kB) Preview
[img]
Preview
Official URL
http://dx.doi.org/10.1109/SCAM.2005.1

Abstract

Long-running, heavily multi-threaded, Java server applications make stringent demands of garbage collector (GC) performance. Synchronisation of all application threads before garbage collection is a significant bottleneck for JVMs that use native threads. We present a new static analysis and a novel GC framework designed to address this issue by allowing independent collection of thread-local heaps. In contrast to previous work, our solution safely classifies objects even in the presence of dynamic class loading, requires neither write-barriers that may do unbounded work, nor synchronisation, nor locks during thread-local collections; our analysis is sufficiently fast to permit its integration into a high-performance, production-quality virtual machine.

Item Type: Conference or workshop item (Paper)
Uncontrolled keywords: Java programming language, Multiprocessing systems, Servers, Synchronization, Virtual reality, Dynamic class loading, Garbage collector (GC), Java server applications, Data reduction
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Sciences > School of Computing > Systems Architecture Group
Depositing User: Richard Jones
Date Deposited: 14 Jul 2015 15:26 UTC
Last Modified: 15 Jul 2015 15:00 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/49521 (The current URI for this page, for reference purposes)
  • Depositors only (login required):

Downloads

Downloads per month over past year