Iterative Probabilistic Performance Prediction for Multi-Application Multiprocessor Systems

Accurate Run-time Performance Prediction for Multi-Application Multi-Processor Systems

Non-preemptive multi-processor platforms are increasingly being developed to support the performance requirements of modern systems with multiple applications. Due to a huge number of possible combinations of these multiple applications, it becomes a challenge to predict their performance in advance. This becomes even more important when applications may be dynamically started and stopped in th...

Stochastic Performance Prediction for Iterative Algorithms in Distributed Environments. Performance Prediction for Iterative Algorithms

The parallelization of certain iterative algorithms is a crucial issue for the eecient solution of large numerical problems. Several theoretical results concerning the suucient conditions for, and speed of, convergence for parallel iterative algorithms are available. However, there is a gap between those results and what is relevant to the user at the application level. The performance characte...

Multiprocessor Performance for Polymorphous Computing Systems

Polymorphous computing architectures are being developed to provide high performance across a wide range of DoD applications. In this paper, we describe a multiprocessor PCA prototype system and provide measured application and communication performance results for a polymorphous architecture.

Performance Issues for Multiprocessor Operating Systems

Framework for Multi-Agent Systems Performance Prediction Process Model: MASP

Multi Agent System is one of the upcoming areas in the research/industry for building complex distributed application. MAS encompass multiple features for distributed application. For complex applications the non-functional requirements has the same importance as functional requirements. The non-functional requirements are performance, reliability, maintainability etc. We are focusing on the pr...