Different techniques for estimating the execution time of parallel applications have been
studied for the last 25 years. These approaches have proposed different methods for …

Automated performance modeling and performance prediction of parallel programs are
highly valuable in many use cases, such as in guiding task management and job …

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

Extractors (as defined by Nisan and Zuckerman) are procedures that use a small number of
truly random bits (called the seed) to extract many (almost) truly random bits from arbitrary …

Grid schedulers require individual activity performance predictions to map workflow activities
on different Grid sites. The effectiveness of the scheduling systems is hampered by …

With the maturity of electronic science (e-science) the scientific applications are growing to
be more complex composed of a set of coordinating tasks with complex dependencies …

Constant advances in CPU, storage, and network virtualization are enabling high-
performance computing (HPC) applications to be efficiently executed on cloud computing …

Traces of MPI communications are used by many performance analysis and visualization
tools. Storing exhaustive traces of large scale MPI applications is infeasible, due to their …

We present DwarfCode, a performance prediction tool for MPI applications on diverse
computing platforms. The goal is to accurately predict the running time of applications for …

OpenMP, with its extended parallelism features and support for radically changing HPC
architectures, spurred to a surge in developing parallel applications among the HPC …