Resource Management for Distributed Memory Multicomputers

In this thesis we explore the problem of resource management for multicomputer systems. A variety of algorithms were developed for different task graph models. We first present a suite of static resource management algorithms. For acyclic graphs, the LAST algorithm provides fast processor allocation and intelligent processor usage. For nondeterministic task graphs, the remap algorithm uses profiling data to iteratively improve the allocation decisions. The remap algorithm provides an efficient, distributed implementation with each processor analyzing the tasks assigned to it. Finally, the template strategy provided a static allocation to dynamic tree-based flow graphs.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2014

Author dc:creator

• Baxter, Jeffrey John

Contributors dc:contributor

• Patel, Janak H.

• Engineering, Electronics and Electrical
• Computer Science

Identifier

(UMI)AAI9305464

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/71975