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The growing gap between processor and memory speeds is motivating the
need for optimization strategies that improve data locality. A major
challenge is to devise techniques suitable for pointer-intensive
applications. This paper presents two techniques aimed at improving
the memory behavior of pointer-intensive applications with dynamic
memory allocation, such as those written in Java. First, we present an
allocation time object placement technique based on the recently
introduced notion of prolific (frequently instantiated) types. We
attempt to co-locate, at allocation time, objects of prolific types
that are connected via object references. Then, we present a novel
locality based graph traversal technique. The benefits of this
technique, when applied to garbage collection (GC), are twofold: (i)
it improves the performance of GC due to better locality during a heap
traversal and (ii) it restructures surviving objects in a way that
enhances locality. On multiprocessors, this technique can further
reduce overhead due to synchronization and false sharing. The
experimental results, on a well-known suite of Java benchmarks
(SPECjvm98, SPECjbb2000, and jOlden), from an implementation of these
techniques in the Jikes RVM, are very encouraging. The object
co-allocation technique improves application performance by up to 21%
(10% on average) in the Jikes RVM configured with a non-copying
mark-and-sweep collector. The locality-based traversal technique
reduces GC times by up to 20% (10% on average) and improves the
performance of applications by up to 14% (6% on average) in the Jikes
RVM configured with a copying semi-space collector. Both techniques
combined can improve application performance by up to 22% (10% on
average) in the Jikes RVM configured with a non-copying mark-and-sweep
collector.
By: Yefim Shuf, Manish Gupta, Hubertus Franke, Jaswinder Pal Singh
Published in: ACM SIGPLAN Notices, volume 37, (no 11), pages 13-25 in 2002
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