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  1. Proceedings of the 2011 ACM SIGPLAN Workshop on Memory Systems Performance and Correctness (MSPC '11)
  2. Deferred gratification: engineering for high performance garbage collection from the get go
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There is nothing wrong with out-of-thin-air: compiler optimization and memory models
Extended sequential reasoning for data-race-free programs
The impact of diverse memory architectures on multicore consumer software: an industrial perspective from the video games domain
Garbage collection for multicore NUMA machines
A programming model for deterministic task parallelism
Data-race exceptions have benefits beyond the memory model
Let there be light!: the future of memory systems is photonics and 3D stacking
Deferred gratification: engineering for high performance garbage collection from the get go
Performance implications of fence-based memory models
Minor memory references matter in collaborative caching
Approximating inclusion-based points-to analysis
How to fit program footprint curves

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Deferred gratification: engineering for high performance garbage collection from the get go

Content Provider ACM Digital Library
Author Jibaja, Ivan McKinley, Kathryn S. Haghighat, Mohammad R. Blackburn, Stephen M.
Abstract Implementing a new programming language system is a daunting task. A common trap is to punt on the design and engineering of exact garbage collection and instead opt for reference counting or conservative garbage collection (GC). For example, AppleScript™, Perl, Python, and PHP implementers chose reference counting (RC) and Ruby chose conservative GC. Although easier to get working, reference counting has terrible performance and conservative GC is inflexible and performs poorly when allocation rates are high. However, high performance GC is central to performance for managed languages and only becoming more critical due to relatively lower memory bandwidth and higher memory latency of modern architectures. Unfortunately, retrofitting support for high performance collectors later is a formidable software engineering task due to their exact nature. Whether they realize it or not, implementers have three routes: (1) forge ahead with reference counting or conservative GC, and worry about the consequences later; (2) build the language on top of an existing managed runtime with exact GC, and tune the GC to scripting language workloads; or (3) engineer exact GC from the ground up and enjoy the correctness and performance benefits sooner rather than later. We explore this conundrum using PHP, the most popular server side scripting language. PHP implements reference counting, mirroring scripting languages before it. Because reference counting is incomplete, the implementors must (a) also implement tracing to detect cyclic garbage, or (b) prohibit cyclic data structures, or (c) never reclaim cyclic garbage. PHP chose (a), AppleScript chose (b), and Perl chose (c). We characterize the memory behavior of five typical PHP programs to determine whether their implementation choice was a good one in light of the growing demand for high performance PHP. The memory behavior of these PHP programs is similar to other managed languages, such as Java™ ---they allocate many short lived objects, a large variety of object sizes, and the average allocated object size is small. These characteristics suggest copying generational GC will attain high performance. Language implementers who are serious about correctness and performance need to understand deferred gratification: paying the software engineering cost of exact GC up front will deliver correctness and memory system performance later.
Starting Page 58
Ending Page 65
Page Count 8
File Format PDF
ISBN 9781450307949
DOI 10.1145/1988915.1988930
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2011-06-05
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Garbage collection Scripting languages Php Heap
Content Type Text
Resource Type Article
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