NDLI: Kindergarten cop: dynamic nursery resizing for GHC

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Kindergarten cop: dynamic nursery resizing for GHC

Content Provider	ACM Digital Library
Author	Castro, Laura Ferreiro, Henrique Hammond, Kevin Janjic, Vladimir
Abstract	Generational garbage collectors are among the most popular garbage collectors used in programming language runtime systems. Their performance is known to depend heavily on choosing the appropriate size of the area where new objects are allocated (the nursery). In imperative languages, it is usual to make the nursery as large as possible, within the limits imposed by the heap size. Functional languages, however, have quite different memory be- haviour. In this paper, we study the effect that the nursery size has on the performance of lazy functional programs, through the interplay between cache locality and the frequency of collections. We demonstrate that, in contrast with imperative programs, having large nurseries is not always the best solution. Based on these re- sults, we propose two novel algorithms for dynamic nursery resiz- ing that aim to achieve a compromise between good cache locality and the frequency of garbage collections. We present an implemen- tation of these algorithms in the state-of-the-art GHC compiler for the functional language Haskell, and evaluate them using an exten- sive benchmark suite. In the best case, we demonstrate a reduction in total execution times of up to 88.5%, or an 8.7 overall speedup, compared to using the production GHC garbage collector. On aver- age, our technique gives an improvement of 9.3% in overall perfor- mance across a standard suite of 63 benchmarks for the production GHC compiler. .
Starting Page	56
Ending Page	66
Page Count	11
File Format	PDF
ISBN	9781450342414
DOI	10.1145/2892208.2892223
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-03-17
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Cache locality Allo- cation area Functional programming Generational garbage collection
Content Type	Text
Resource Type	Article

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