A comparison of task pools for dynamic load balancing of irregular algorithms: Research Articles

Authors:
Matthias Korch;Thomas Rauber
Affiliations:
Faculty of Mathematics, Physics and Computer Science, University of Bayreuth, Bayreuth, Germany;Faculty of Mathematics, Physics and Computer Science, University of Bayreuth, Bayreuth, Germany
Venue:
Concurrency and Computation: Practice & Experience
Year:
2003

Citing 0
Cited 9

Performance Evaluation of Task Pools Based on Hardware Synchronization

Proceedings of the 2004 ACM/IEEE conference on Supercomputing
Carbon: architectural support for fine-grained parallelism on chip multiprocessors

Proceedings of the 34th annual international symposium on Computer architecture
On dynamic load balancing on graphics processors

Proceedings of the 23rd ACM SIGGRAPH/EUROGRAPHICS symposium on Graphics hardware
Evaluation of OpenMP task scheduling strategies

IWOMP'08 Proceedings of the 4th international conference on OpenMP in a new era of parallelism
A comparison of task pool variants in OpenMP and a proposal for a solution to the busy waiting problem

IWOMP'05/IWOMP'06 Proceedings of the 2005 and 2006 international conference on OpenMP shared memory parallel programming
A runtime implementation of OpenMP tasks

IWOMP'11 Proceedings of the 7th international conference on OpenMP in the Petascale era
Applicability of load balancing strategies to data-parallel embedded runge-kutta integrators

Euro-Par'06 Proceedings of the 12th international conference on Parallel Processing
Speeding up OpenMP tasking

Euro-Par'12 Proceedings of the 18th international conference on Parallel Processing
Hardware support for fine-grained event-driven computation in Anton 2

Proceedings of the eighteenth international conference on Architectural support for programming languages and operating systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Since a static work distribution does not allow for satisfactory speed-ups of parallel irregular algorithms, there is a need for a dynamic distribution of work and data that can be adapted to the runtime behavior of the algorithm. Task pools are data structures which can distribute tasks dynamically to different processors where each task specifies computations to be performed and provides the data for these computations. This paper discusses the characteristics of task-based algorithms and describes the implementation of selected types of task pools for shared-memory multiprocessors. Several task pools have been implemented in C with POSIX threads and in Java. The task pools differ in the data structures to store the tasks, the mechanism to achieve load balance, and the memory manager used to store the tasks. Runtime experiments have been performed on three different shared-memory systems using a synthetic algorithm, the hierarchical radiosity method, and a volume rendering algorithm. Copyright © 2004 John Wiley & Sons, Ltd.