The main goal of parallel/distributed applications is to solve a considered problem as fast as possible using the minimum amount of system resources. In this context, the application performance becomes a crucial issue and developers of parallel/distributed applications must optimize them to provide high performance computation. Typically, to improve performance, developers analyze the application behavior, search for bottlenecks, determine their causes and change the source code. In this paper, we present the dynamic, automatic tuning approach. This approach aims at automating these tasks and minimizing user intervention. An application is monitored, its performance bottlenecks are detected and it is modified automatically during the execution, without recompiling or re-running it. The modifications introduced adapt the application behavior to the changing conditions. This paper describes design and implementation of the MATE environment (Monitoring, Analysis and Tuning Environment), which we have developed as a step towards dynamically tuning parallel/distributed applications. © 2007 Elsevier Inc. All rights reserved.
|Journal||Journal of Parallel and Distributed Computing|
|Publication status||Published - 1 Apr 2007|
- Automatic performance analysis
- Dynamic instrumentation
- Dynamic tuning
- Parallel/distributed application