A new memory slowdown model for the characterization of computing systems

Authors:
Rodrigo Fernandes de Mello;Luciano José Senger;Kuan-Ching Li;Laurence Tianruo Yang
Affiliations:
Dept. of Computer Science - ICMC, University of São Paulo, São Carlos, SP Brazil;Dept. of Information Technology, University of Ponta Grossa, PR Brazil;Dept. of Computer Science (CSIE), Providence University, Shalu, Taichung Taiwan;Dept. of Computer Science, St. Francis Xavier University, Antigonish, NS Canada
Venue:
PaCT'07 Proceedings of the 9th international conference on Parallel Computing Technologies
Year:
2007

Citing 15
Cited 0

Quantitative system performance: computer system analysis using queueing network models

Quantitative system performance: computer system analysis using queueing network models
A guide to simulation (2nd ed.)

A guide to simulation (2nd ed.)
Statistics: concepts and applications

Statistics: concepts and applications
On the parallel implementation of Goldberg's maximum flow algorithm

SPAA '92 Proceedings of the fourth annual ACM symposium on Parallel algorithms and architectures
LogP: towards a realistic model of parallel computation

PPOPP '93 Proceedings of the fourth ACM SIGPLAN symposium on Principles and practice of parallel programming
An approach to scalability study of shared memory parallel systems

SIGMETRICS '94 Proceedings of the 1994 ACM SIGMETRICS conference on Measurement and modeling of computer systems
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing

PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
Parallel programming with MPI

Parallel programming with MPI
Execution-driven simulators for parallel systems design

Proceedings of the 29th conference on Winter simulation
An Opportunity Cost Approach for Job Assignment in a Scalable Computing Cluster

IEEE Transactions on Parallel and Distributed Systems
Computer Performance Modeling Handbook

Computer Performance Modeling Handbook
Towards a Communication Characterization Methodology for Parallel Applications

HPCA '97 Proceedings of the 3rd IEEE Symposium on High-Performance Computer Architecture
Analysis on the Significant Information to Update the Tables on Occupation of Resources by Using a Peer-to-Peer Protocol

HPCS '02 Proceedings of the 16th Annual International Symposium on High Performance Computing Systems and Applications
SPLASH: Stanford parallel applications for shared-memory

SPLASH: Stanford parallel applications for shared-memory
Communication characteristics of large-scale scientific applications for contemporary cluster architectures

Journal of Parallel and Distributed Computing - Special section best papers from the 2002 international parallel and distributed processing symposium

Quantified Score

Hi-index	0.00

Visualization

Abstract

Performance measurements were extensively conducted to characterize parallel computer systems by using modelling and experiments. By analyzing them, we corroborate current models did not provide precise memory characterization. After detailed result observation, we conclude that the performance slowdown is linear when using the main memory, and exponential when using the virtual memory. In this paper, we propose a characterization model composed of two regressions which represent the slowdown caused by memory usage. Experimental results confirm the memory slowdown model improves the quality of computing system characterization, allowing to carry out simulations and the use of such results as a way to design real systems, minimizing project design costs.