Personal tools
You are here: Home Publications Cross-Architecture Performance Predictions for Scientific Applications Using Parameterized Models
Document Actions

Gabriel Marin and John Mellor-Crummey (2004)

Cross-Architecture Performance Predictions for Scientific Applications Using Parameterized Models

In: Proceedings of the Joint International Conference on Measurement and Modeling of Computer Systems, pp. 2-13, New York, NY, ACM Press.

This paper describes a toolkit for semi-automatically measuring and modeling static and dynamic characteristics of applications in an architecture-neutral fashion. For predictable applications, models of dynamic characteristics have a convex and differentiable profile. Our toolkit operates on application binaries and succeeds in modeling key application characteristics that determine program performance. We use these characterizations to explore the interactions between an application and a target architecture. We apply our toolkit to SPARC binaries to develop architecture-neutral models of computation and memory access patterns of the ASCI Sweep3D and the NAS SP, BT and LU benchmarks. From our models, we predict the L1, L2 and TLB cache miss counts as well as the overall execution time of these applications on an Origin 2000 system. We evaluate our predictions by comparing them against measurements collected using hardware performance counters.

by admin last modified 2007-12-10 21:05
« September 2010 »
Su Mo Tu We Th Fr Sa
1234
567891011
12131415161718
19202122232425
2627282930
 

Powered by Plone

LACSI Collaborators include:

Rice University LANL UH UNM UIUC UNC UTK