Algorithms for scheduling task-based applications onto heterogeneous many-core architectures

Michel A. Kinsy, Srinivas Devadas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

In this paper we present an Integer Linear Programming (ILP) formulation and two non-iterative heuristics for scheduling a task-based application onto a heterogeneous many-core architecture. Our ILP formulation is able to handle different application performance targets, e.g., low execution time, low memory miss rate, and different architectural features, e.g., cache sizes. For large size problem where the ILP convergence time may be too long, we propose a simple mapping algorithm which tries to spread tasks onto as many processing units as possible, and a more elaborate heuristic that shows good mapping performance when compared to the ILP formulation. We use two realistic power electronics applications to evaluate our mapping techniques on full RTL many-core systems consisting of eight different types of processor cores.

Original languageEnglish (US)
Title of host publication2014 IEEE High Performance Extreme Computing Conference, HPEC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479962334
DOIs
StatePublished - Feb 11 2014
Externally publishedYes
Event2014 IEEE High Performance Extreme Computing Conference, HPEC 2014 - Waltham, United States
Duration: Sep 9 2014Sep 11 2014

Publication series

Name2014 IEEE High Performance Extreme Computing Conference, HPEC 2014

Conference

Conference2014 IEEE High Performance Extreme Computing Conference, HPEC 2014
Country/TerritoryUnited States
CityWaltham
Period9/9/149/11/14

ASJC Scopus subject areas

  • Software

Fingerprint

Dive into the research topics of 'Algorithms for scheduling task-based applications onto heterogeneous many-core architectures'. Together they form a unique fingerprint.

Cite this