Optimal parallel merging and sorting without memory conflicts
IEEE Transactions on Computers
Implementing Quicksort programs
Communications of the ACM
A microbenchmark suite for OpenMP 2.0
ACM SIGARCH Computer Architecture News - Special Issue: PACT 2001 workshops
ICS '03 Proceedings of the 17th annual international conference on Supercomputing
Support for OpenMP tasks in Nanos v4
CASCON '07 Proceedings of the 2007 conference of the center for advanced studies on Collaborative research
An adaptive cut-off for task parallelism
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
OpenMP tasks in IBM XL compilers
CASCON '08 Proceedings of the 2008 conference of the center for advanced studies on collaborative research: meeting of minds
IEEE Transactions on Parallel and Distributed Systems
ICPP '09 Proceedings of the 2009 International Conference on Parallel Processing
CLOMP: accurately characterizing OpenMP application overheads
IWOMP'08 Proceedings of the 4th international conference on OpenMP in a new era of parallelism
Evaluation of OpenMP task scheduling strategies
IWOMP'08 Proceedings of the 4th international conference on OpenMP in a new era of parallelism
Computing on multi-core platform: performance issues
Proceedings of the 2011 International Conference on Communication, Computing & Security
A microbenchmark suite for OpenMP tasks
IWOMP'12 Proceedings of the 8th international conference on OpenMP in a Heterogeneous World
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As of 2008, the OpenMP 3.0 standard includes task support allowing programmers to exploit irregular parallelism. Although several compilers are providing support for this new feature there has not been extensive investigation into the real possibilities of this extension. Several papers have discussed the programming model itself while other papers have discussed design and implementation on different platforms. There are also papers demonstrating performance results using well known kernel applications. This paper presents an analysis of the OpenMP tasking model possibilities, using the IBM XL compiler implementation. Using different parameters such as the number of tasks, task granularity and parallelism pattern, this paper explores how such parameters can affect the average performance and identifies the limits of the OpenMP tasking model.