Title
Characterizing Resource Allocation Heuristics For Heterogeneous Computing Systems
Abstract
In many distributed computing environments, collections of applications need to be processed using a set of heterogeneous computing (HC) resources to maximize some performance goal. An important research problem in these environments is how to assign resources to applications (matching) and order the execution of the applications (scheduling) so as to maximize some performance criterion without violating any constraints. This process of matching and scheduling is called mapping. To make meaningful comparisons among mapping heuristics, a system designer needs to understand the assumptions made by the heuristics for (1) the model used for the application and communication tasks, (2) the model used for system platforms, and (3) the attributes of the mapping heuristics. This chapter presents a three-part classification scheme (3PCS) for HC systems. The 3PCS is useful for researchers who want to (a) understand a mapper given in the literature, (b) describe their design of a mapper more thoroughly by using a common standard, and (c) select a mapper to match a given real-world environment. © 2005 Elsevier Inc. All rights reserved.
Publication Date
12-1-2005
Publication Title
Advances in Computers
Volume
63
Number of Pages
91-128
Document Type
Review
Personal Identifier
scopus
DOI Link
https://doi.org/10.1016/S0065-2458(04)63003-8
Copyright Status
Unknown
Socpus ID
22144438930 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/22144438930
STARS Citation
Ali, Shoukat; Braun, Tracy D.; and Siegel, Howard Jay, "Characterizing Resource Allocation Heuristics For Heterogeneous Computing Systems" (2005). Scopus Export 2000s. 3511.
https://stars.library.ucf.edu/scopus2000/3511