Task Packing: Getting the Best from MPI Unbalanced Applications
Gladys Utrera, Montse Farreras, Jordi Fornes · 2017
In this work we propose a Taskpacking mechanism that concentrate the idle cycles of unbalanced applications in such a way that one or more cores are freed from execution. To achieve that we stress the cores with just useful work of the parallel application tasks, provided performance is not degraded. Tasks are "packed" in a minimum number of cores using oversubscription. In order to do the task mapping to cores and the computation of the minimum number of cores we apply the Subset Sum algorithm, which is a particular case of the Knapsack problem. Our experiments demonstrate that our task packing using oversubscription without performance degradation is possible. In this sense, the mechanism is able to make accurate allocation decisions leaving room for executing other applications or just keeping other cores idle. Our proposal is scalable as the task allocation decisions are based just on local information and task migrations are performed only within each node.