Paper Info
Title
Parallelization of dynamic languages: synchronizing built-in collections
Abstract
Dynamic programming languages such as Python and Ruby are widely used, and much effort is spent on making them efficient. One substantial research effort in this direction is the enabling of parallel code execution. While there has been significant progress, making dynamic collections efficient, scalable, and thread-safe is an open issue. Typical programs in dynamic languages use few but versatile collection types. Such collections are an important ingredient of dynamic environments, but are difficult to make safe, efficient, and scalable. In this paper, we propose an approach for efficient and concurrent collections by gradually increasing synchronization levels according to the dynamic needs of each collection instance. Collections reachable only by a single thread have no synchronization, arrays accessed in bounds have minimal synchronization, and for the general case, we adopt the Layout Lock paradigm and extend its design with a lightweight version that fits the setting of dynamic languages. We apply our approach to Ruby's Array and Hash collections. Our experiments show that our approach has no overhead on single-threaded benchmarks, scales linearly for Array and Hash accesses, achieves the same scalability as Fortran and Java for classic parallel algorithms, and scales better than other Ruby implementations on Ruby workloads.
Year
DOI
Venue
2018
10.1145/3276478
Proceedings of the ACM on Programming Languages
Keywords
Field
DocType
Collections,Concurrency,Dynamically-typed languages,Graal,Ruby,Thread Safety,Truffle
Concurrency,Parallel algorithm,Computer science,Parallel computing,Hash function,Thread safety,Java,Python (programming language),Computer programming,Scalability
Journal
Volume
Issue
ISSN
2
OOPSLA
2475-1421
Citations 
PageRank 
References 
0
0.34
23
Authors
5
Name
Order
Citations
PageRank
Benoit Daloze190.87
Arie Tal220.70
Stefan Marr312421.54
Hanspeter Mössenböck478188.17
Erez Petrank51601107.96