This paper presents a scheme to optimize the mapping of HPC applications to a set of hybrid dedicated and cloud resources. First, we characterize application performance on dedica...
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Abstract. As an alternative to message passing, Rochester's InterWeave system allows the programmer to map shared segments into programs spread across heterogeneous, distribut...
The Self-Organising Map is a popular unsupervised neural network model which has been used successfully in various contexts for clustering data. Even though labelled data is not re...
In this article, we revisit the problem of scheduling dynamically generated directed acyclic graphs (DAGs) of multi-processor tasks (M-tasks). A DAG is a basic model for expressin...