Traditional means of gathering performance data are tracing, which is limited by the
available storage, and profiling, which has limited accuracy. Performance modeling is often …

In this paper we studied performance predictions for parallel scientific applications on a
homogeneous cluster of workstations. Performance prediction is important for analyses of …

The increase of computer networks speed paired with the ubiquity of inexpensive, yet fast
and generously equipped hardware offers many organizations an affordable way to …

This work proposes a new technique for performance evaluation to predict performance of
parallel programs across diverse and complex systems. In this work the term system is …

Predicting distributed application performance is a constant challenge to researchers, with
an increased difficulty when heterogeneous systems are involved. Research conducted so …

Performance prediction for parallel applications running in heterogeneous clusters is difficult
to accomplish due to the unpredictable resource contention patterns that can be found in …

Accurately modeling and predicting performance for large-scale applications becomes
increasingly difficult as system complexity scales dramatically. Analytic predictive models …

Predicting the performance of parallel scientific applications is becoming increasingly
complex. Our goal was to characterize the behavior of message-passing applications on …

Predicting the execution time of parallel applications in High Performance Computing (HPC)
clusters has served different objectives, including helping developers to find relevant areas …