2015 23rd Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP) (2015)
March 4, 2015 to March 6, 2015
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/PDP.2015.65
High-level data-structures are an important foundation for most applications. With the rise of multicores, there is a trend of supporting data-parallel collection operations in general purpose programming languages. However, these operations often incur high-level abstraction and scheduling penalties. We present a generic data-parallel collections design based on work-stealing for shared-memory architectures that overcomes abstraction penalties through call site specialization of data-parallel operation instances. Moreover, we introduce work-stealing iterators that allow more fine-grained and efficient work-stealing. By eliminating abstraction penalties and making work-stealing data-structure-aware we achieve several dozen times better performance compared to existing JVM-based approaches.
Kernel, Java, Parallel processing, Reactive power, Throughput, Contracts, Scheduling
A. Prokopec, D. Petrashko and M. Odersky, "Efficient Lock-Free Work-Stealing Iterators for Data-Parallel Collections," 2015 23rd Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), Turku, Finland, 2015, pp. 248-252.