Mapping Tasks to Processors in Heterogeneous Multiprocessor Architectures: The MATEHa Algorithm

An automatic task-to-processor mapping algorithm is analyzed in parallel systems that run over loosely coupled distributed architectures. This research is based on the TTIGHa model that allows predicting parallel application performance running over heterogeneous architectures. In particular, the he...

Full description

Saved in:
Bibliographic Details
Main Authors: De Giusti, L., Chichizola, F., Naiouf, M., De Giusti, A.
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Application software
Clustering algorithms
Computer architecture
Computer science
Concurrent computing
Costs
Distributed Architectures
Distributed computing
Heterogeneity Performance Prediction Models
Parallel Systems
Predictive models
Robustness
Task-to-processor Mapping
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:An automatic task-to-processor mapping algorithm is analyzed in parallel systems that run over loosely coupled distributed architectures. This research is based on the TTIGHa model that allows predicting parallel application performance running over heterogeneous architectures. In particular, the heterogeneity of both processors and communications is taken into consideration. From the results obtained with the TTIGHa model, the MATEHa algorithm for task-to-processors assignment is presented and its implementation is analyzed. Experimental results working on subsets of two-cluster heterogeneous machines are presented, analyzing the resulting mapping scheme with MATEHa and two previous mapping methods: MATE and HEFT. Finally, the algorithm robustness is considered based on the variation of model parameters: inter-process communication times and processing times.
ISSN:1522-4902
2691-0632
DOI:10.1109/SCCC.2008.11