Performance is a key issue in the development of parallel/distributed applications. The main goal of these applications is to solve the considered problem as fast as possible utilizing a certain minimum of parallel system capacities. Therefore, developers must optimize these applications if they are to fulfill the promise of high performance computation. To improve performance, programmers search for bottlenecks by analyzing application behavior, finding problems and solving them by changing the source code. These tasks are especially difficult for non-expert programmers. Current approaches require developers to perform optimizations manually and to have a high degree of experience. Moreover, applications may be executed in dynamic environments. Therefore, it is necessary to provide tools that automatically carry out the optimization process by adapting application execution to changing conditions. This paper presents the dynamic tuning approach that addresses these issues. We also describe an environment called MATE (Monitoring, Analysis and Tuning Environment), which provides dynamic tuning of applications. © Springer-Verlag 2004.
|Journal||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Publication status||Published - 1 Dec 2004|