Performance prediction of PVM programs

Author

Steed, Michael R. ; Clement, Mark J.

Author_Institution

Dept. of Comput. Sci., Brigham Young Univ., Provo, UT, USA

fYear

1996

fDate

15-19 Apr 1996

Firstpage

803

Lastpage

807

Abstract

As workstation clusters gain popularity as a parallel computing platform, there is an increasing need for performance tools that support these platforms. Performance prediction is important for performance analysis of scalable parallel applications. Although there are several performance tools available that work with PVM programs, none are capable of performance prediction. We have developed the APACHE (Automated PVM Application Characterization Environment) performance prediction system for PVM programs running on workstation clusters. We review the system implementation and present some experimental results obtained with the system

Keywords

local area networks; parallel programming; program debugging; software libraries; software performance evaluation; software reusability; software tools; APACHE; Automated PVM Application Characterization Environment; PVM programs; Parallel Virtual Machine; message passing library; parallel computing; parallel programming; performance analysis; performance tools; program debugging; scalable parallel applications; software performance prediction; workstation clusters; Costs; Data visualization; Debugging; Hardware; Libraries; Message passing; Parallel processing; Performance analysis; Performance gain; Predictive models; Runtime; Workstations;

fLanguage

English

Publisher

ieee

Conference_Titel

Parallel Processing Symposium, 1996., Proceedings of IPPS '96, The 10th International

Conference_Location

Honolulu, HI

Print_ISBN

0-8186-7255-2

Type

conf

DOI

10.1109/IPPS.1996.508151

Filename

508151