Source-level global optimizations for fine-grain distributed shared memory systems

Abstract

This paper describes and evaluates the use of aggressive static analysis in Jackal, a fine-grain Distributed Shared Memory (DSM) system for Java. Jackal uses an optimizing, source-level compiler rather than the binary rewriting techniques employed by most other fine-grain DSM systems. Source-level analysis makes existing access-check optimizations (e.g., access-check batching) more effective and enables two novel fine-grain DSM optimizations: object-graph aggregation and automatic computation migration.