Comparing the Optimal Performance of Multiprocessor Architectures

Document type: Conference Papers
Peer reviewed: Yes
Author(s): Lars Lundberg, Kamilla Klonowska, Magnus Broberg, Håkan Lennerstad
Title: Comparing the Optimal Performance of Multiprocessor Architectures
Conference name: 21st IASTED International Multi-Conference Applied Informatics
Year: 2003
Pagination: 750-760
ISBN: 0889863415
Publisher: Int. Assoc. of Science and Technology for Development, Calgery - Alberta, T3B OM6, Canada
City: Innsbruck, Austria
Organization: Blekinge Institute of Technology
Department: Department of Software Engineering and Computer Science (Institutionen för programvaruteknik och datavetenskap)
Dept. of Software Engineering and Computer Science S-372 25 Ronneby
+46 455 38 50 00
http://www.bth.se/eng/ipd/
Authors e-mail: lars.lundberg@bth.se, kamilla.klonowska@bth.se, magnus.broberg@bth.se, hakan.lennerstad@bth.se
Language: English
Abstract: Consider a parallel program with n processes and a synchronization granularity z. Consider also two multiprocessors: a multiprocessor with q processors and run-time reallocation of processes to processors, and a multiprocessor with k processors and no run-time reallocation. There is an inter processor communication delay of t time units for the system with no run-time reallocation. In this paper we define a function g(n,k,q,t,z) such that the minimum completion time for all programs with n processes and a granularity z is at most g(n,k,q,t,z) times longer using the system with no reallocation and k processors compared to using the system with q processors and run-time reallocation. We assume optimal allocation and scheduling of processes to processors. The function g(n,k,q,t,z) is optimal in the sense that there is at least one program, with n processes and a granularity z, such that the ratio is exactly g(n,k,q,t,z). We also validate our results using measurements on distributed and multiprocessor Sun/Solaris environments.
Subject: Computer Science\Computersystems
Keywords: Multiprocessing systems, Computer architecture, Resource allocation, Scheduling, Synchronization, Computational complexity, Distributed system, Multiprocessors, Optimal bounds
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