DocumentCode
2484483
Title
Work-first and help-first scheduling policies for async-finish task parallelism
Author
Guo, Yi ; Barik, Rajkishore ; Raman, Raghavan ; Sarkar, Vivek
Author_Institution
Dept. of Comput. Sci., Rice Univ., Houston, TX, USA
fYear
2009
fDate
23-29 May 2009
Firstpage
1
Lastpage
12
Abstract
Multiple programming models are emerging to address an increased need for dynamic task parallelism in applications for multicore processors and shared-address-space parallel computing. Examples include OpenMP 3.0, Java Concurrency Utilities, Microsoft Task Parallel Library, Intel Thread Building Blocks, Cilk, X10, Chapel, and Fortress. Scheduling algorithms based on work stealing, as embodied in Cilk´s implementation of dynamic spawn-sync parallelism, are gaining in popularity but also have inherent limitations. In this paper, we address the problem of efficient and scalable implementation of X10´s async-finish task parallelism, which is more general than Cilk´s spawn-sync parallelism. We introduce a new work-stealing scheduler with compiler support for async-finish task parallelism that can accommodate both work-first and help-first scheduling policies. Performance results on two different multicore SMP platforms show significant improvements due to our new work-stealing algorithm compared to the existing work-sharing scheduler for X10, and also provide insights on scenarios in which the help-first policy yields better results than the work-first policy and vice versa.
Keywords
parallel programming; scheduling; task analysis; Chapel; Cilk; Fortress; Intel Thread Building Blocks; Java Concurrency Utilities; Microsoft Task Parallel Library; OpenMP 3.0; X10; async-finish task parallelism; compiler support; dynamic spawn-sync parallelism; dynamic task parallelism; help-first scheduling policies; multicore processor; programming model; shared-address-space parallel computing; work stealing; work-first scheduling policies; Concurrent computing; Dynamic programming; Java; Libraries; Multicore processing; Parallel processing; Parallel programming; Processor scheduling; Scheduling algorithm; Yarn;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel & Distributed Processing, 2009. IPDPS 2009. IEEE International Symposium on
Conference_Location
Rome
ISSN
1530-2075
Print_ISBN
978-1-4244-3751-1
Electronic_ISBN
1530-2075
Type
conf
DOI
10.1109/IPDPS.2009.5161079
Filename
5161079
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