id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_gcygeykq7ffsnenhntlew223ma	Bérenger Bramas	Improving parallel executions by increasing task granularity in task-based runtime systems using acyclic DAG clustering	2020	26	.pdf	application/pdf	16204	3471	89	we study an existing clustering/partitioning strategy to speed up the parallel execution Keywords Task-based, Graph, DAG, Clustering, Partitioning paper, is to investigate how to cluster the nodes of task graphs to increase the granularity of between the cluster of nodes should ensure to be executable as a graph of tasks, and keep explain why most existing algorithms do not solve the DAG of tasks clustering problem. time of the resulting graph in parallel considering a given number of threads and runtime The granularity problem of the DAG of tasks with a focus on the parallel execution has hardware without overhead, any clustering of tasks will reduce the degree of parallelism a cluster, the algorithm first picks one of the ready tasks, based on a heuristic that we in a cluster, the algorithm releases its dependencies and potentially adds new ready tasks Table 2 Speedup obtained by clustering the graphs on emulated executions for GDCA and GDCAv2.	./cache/work_gcygeykq7ffsnenhntlew223ma.pdf	./txt/work_gcygeykq7ffsnenhntlew223ma.txt