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Title: Efficient tree-traversals: reconciling parallelism and dense data representations
Recent work showed that compiling functional programs to use dense, serialized memory representations for recursive algebraic datatypes can yield significant constant-factor speedups for sequential programs. But serializing data in a maximally dense format consequently serializes the processing of that data, yielding a tension between density and parallelism. This paper shows that a disciplined, practical compromise is possible. We present Parallel Gibbon, a compiler that obtains the benefits of dense data formats and parallelism. We formalize the semantics of the parallel location calculus underpinning this novel implementation strategy, and show that it is type-safe. Parallel Gibbon exceeds the parallel performance of existing compilers for purely functional programs that use recursive algebraic datatypes, including, notably, abstract-syntax-tree traversals as in compilers.  more » « less
Award ID(s):
1725672 1919197
NSF-PAR ID:
10315715
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Proceedings of the ACM on Programming Languages
Volume:
5
Issue:
ICFP
ISSN:
2475-1421
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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