Predicting Application Behavior in Large Scale Shared-memory Multiprocessors

In this paper we present an analytical-based framework for parallel program performance prediction. The main thrust of this work is to provide a means for treating realistic applications within a single unied framework. Our approach is based upon the specication of a set of non-linear equations which describe the application, processor conguration, network and memory operations. These equations are solved iteratively since the application execution rate depends on the communication latencies. The iterative solution technique is found to be ecient as it typically requires only few iterations to reach convergence. Our modeling methodology achieves a good balance between ion and accuracy. This is attained by accounting for both time and space dimensions of memory references, while maintaining a simple description of the workload. We demonstrate both the practicality and the accuracy of our approach by comparing predicted results with measurements taken on a commercial multiprocessor ...

• Type: Conference
• Year: 1995
• Where: SC
• Authors: Karim Harzallah, Kenneth C. Sevcik
• Keywords: Applied Computing, Iterative Solution Technique, Program Performance Prediction, SC 1995, Uni Ed Framework