As workstation clusters gain popularity as a parallel computing platform, there is an
increasing need for performance tools that support these platforms. Performance prediction …

Advances in computer technology, encompassed with fast emerging of multicore processor
technology, have made the many-core personal computers available and more affordable …

This paper presents a framework based on an user driven methodology to obtain analytical
models on parallel systems and, in particular, clusters. This framework consists of two …

Executing message-passing parallel applications on a large number of resources in an
efficient way is not a trivial task. Due to the complex interaction between the parallel …

Performance modeling can be utilized in a number of scenarios, starting from finding
performance bugs to the scalability study of applications. Existing dynamic and static …

Networks of workstations (NOW) are receiving increased attention as a viable platform for
high performance parallel computations. Heterogeneity and time-sharing are two …

This paper describes the general methodology of specifying parallel systems within the
PAPS (Performance Analysis of Parallel Systems) toolset and presents a case study that …

Modeling and predicting the performance of HPC applications is exceedingly important for
several purposes. These incorporate scheduling and managing tasks, understanding …

This paper proposes causal models for enhancing the performance analysis of parallel
programs. Causal models make the relations among the variables of interest explicit. By …

Predictions based on analytical performance models can be used on efficient scheduling
policies in order to select adequate resources for an optimal execution in terms of …