Understanding some simple processor-performance limits
IBM Journal of Research and Development - Special issue: performance analysis and its impact on design
Proceedings of the 1st international workshop on Software and performance
Performance analysis using the MIPS R10000 performance counters
Supercomputing '96 Proceedings of the 1996 ACM/IEEE conference on Supercomputing
The MIPS R10000 Superscalar Microprocessor
IEEE Micro
A Factorial Performance Evaluation for Hierarchical Memory Systems
IPPS '99/SPDP '99 Proceedings of the 13th International Symposium on Parallel Processing and the 10th Symposium on Parallel and Distributed Processing
Instruction-Level Microprocessor Modeling of Scientific Applications
ISHPC '99 Proceedings of the Second International Symposium on High Performance Computing
A Framework for Statistical Modeling of Superscalar Processor Performance
HPCA '97 Proceedings of the 3rd IEEE Symposium on High-Performance Computer Architecture
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A hybrid approach that utilizes both statistical techniques and empirical methods seeks to provide more information about the performance of an application. In this paper, we present a general approach to creating hybrid models of this type. We show that for the scientific applications of interest, the scaled performance is somewhat predictable due to the regular characteristics of the measured codes. Furthermore, the resulting method encourages streamlined performance evaluation by determining which analysis steps may provide further insight to code performance.