University of Hertfordshire

From the same journal

By the same authors

Documents

View graph of relations
Original languageEnglish
Article number1650011
Number of pages26
JournalParallel Processing Letters
Journal publication date21 Sep 2016
Volume26
Issue3
DOIs
StatePublished - 21 Sep 2016

Abstract

This is an evaluation study of the expressiveness provided and the performance delivered by the coordination language S-NET in comparison to Intel’s Concurrent Collections (CnC). An S-NET application is a network of black-box compute components connected through anonymous data streams, with the standard input and output streams linking the application to the environment. Our case study is based on two applications: a face detection algorithm implemented as a pipeline of feature classifiers and a numerical algorithm from the linear algebra domain, namely Cholesky decomposition. The selected applications are representative and have been selected by Intel researchers as evaluation testbeds for CnC in the past. We implement various versions of both algorithms in S-NET and compare them with equivalent CnC implementations, both with and without tuning, previously published by the CnC community. Our experiments on a large-scale server system demonstrate that S-Net delivers very similar scalability and absolute performance on the studied examples as tuned CnC codes do, even without specific tuning. At the same time, S-Net does achieve a much more complete separation of concerns between compute and coordination layers than CnC even intends to.

Notes

Electronic version of an article published as Pavel Zaichenkov et al, Parallel Processing Letters, Vol. 26 (3), 2016, 24 pages. Under embargo. Embargo end date: 21 September 2017. DOI: http://www.worldscientific.com/doi/abs/10.1142/S0129626416500110 © 2016 World Scientific Publishing Company http://www.worldscientific.com/worldscinet/ppl

ID: 9998381