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
Link To Document :
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