id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_3snzfdkn7bb6hpxhca6z5amcfa	Bérenger Bramas	Impact study of data locality on task-based applications through the Heteroprio scheduler	2019	25	.pdf	application/pdf	11065	1268	69	Impact study of data locality on task-based applications Impact study of data locality on task-based applications through the Heteroprio different memory nodes can be evaluated without looking at the tasks' dependencies. Keywords Scheduling, Task-based, Starpu, HPC, Data locality Our first step in managing data locality is to subdivide each bucket into M different tasklists and set up one list for each of the M memory nodes. the tasks of the bucket index b that we consider local to the memory node m. locality of a task regarding the memory nodes and the distribution of the data it uses. Table 1 Examples of memory node selection by the proposed DLAF for different tasks and data configurations. Impact study of data locality on task-based applications through the Heteroprio scheduler Impact study of data locality on task-based applications through the Heteroprio scheduler Impact study of data locality on task-based applications through the Heteroprio scheduler	./cache/work_3snzfdkn7bb6hpxhca6z5amcfa.pdf	./txt/work_3snzfdkn7bb6hpxhca6z5amcfa.txt