Team, Visitors, External Collaborators
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
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Section: New Software and Platforms


Keywords: Graph algorithmics - Clustering - Partitioning

Scientific Description: This library is a clustering algorithm to create macro-tasks in a DAG of tasks. It extends a clustering/partitioning strategy proposed by Rossignon et al. to speed up the parallel execution of a task-based application. In this package, we provide two additional heuristics to this algorithm, which have been validated on a large graph set. The objective of clustering the nodes of task graphs is to increase the granularity of the tasks and thus obtain faster execution by mitigating the overhead from the management of the dependencies. An important asset of this approach is that working at the graph level allows us to create a generic method independent of the application and of what is done at the user level, but also independent of the task-based runtime system that could be used underneath.

Functional Description: Acyclic Dag Partitioning.