Premium
Palirria: accurate on‐line parallelism estimation for adaptive work‐stealing
Author(s) -
Varisteas Georgios,
Brorsson Mats
Publication year - 2016
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.3630
Subject(s) - computer science , multiprocessing , scheduling (production processes) , fork (system call) , parallelism (grammar) , multi core processor , parallel computing , resource (disambiguation) , distributed computing , real time computing , operating system , computer network , operations management , economics
Summary We present Palirria, a self‐adapting work‐stealing scheduling method for nested fork/join parallelism that can be used to estimate the number of utilizable workers and self‐adapt accordingly. The estimation mechanism is optimized for accuracy, minimizing the requested resources without degrading performance. We implemented Palirria for both the Linux and Barrelfish operating systems and evaluated it on two platforms: a 48‐core Non‐Uniform Memory Access (NUMA) multiprocessor and a simulated 32‐core system. Compared with state‐of‐the‐art, we observed higher accuracy in estimating resource requirements. This leads to improved resource utilization and performance on par or better to executing with fixed resource allotments. Copyright © 2015 John Wiley & Sons, Ltd.