Scalability Model Based on the Concept of Granularity

TL;DR

This paper proposes a new scalability model based on application granularity, offering an efficient alternative to traditional performance evaluation methods by decomposing execution time into computation and overheads.

Contribution

It introduces a novel approach to evaluate parallel application scalability through granularity analysis, reducing the need for multiple executions and extensive data analysis.

Findings

Efficient scalability evaluation using granularity decomposition.

Reduced time and effort compared to traditional wall-clock measurements.

Potential for improved resource utilization in parallel computing.

Abstract

In the recent years it can be observed increasing popularity of parallel processing using multi-core processors, local clusters, GPU and others. Moreover, currently one of the main requirements the IT users is the reduction of maintaining cost of the computer infrastructure. It causes that the performance evaluation of the parallel applications becomes one of the most important problem. Then obtained results allows efficient use of available resources. In traditional methods of performance evaluation the results are based on wall-clock time measurements. This approach requires consecutive application executions and includes a time-consuming data analysis. In the paper an alternative approach is proposed. The decomposition of parallel application execution time onto computation time and overheads related to parallel execution is use to calculate the granularity of application and then determine its efficiency. Finally the application scalability can be evaluates.