[Abstract]: The Deep Learning (DL) community found in pruning techniques a good way to reduce the models' resource and energy consumption. These techniques lead to smaller sparse models, but sparse computations in GPUs ...

[Abstract] Data-flow computing is a natural and convenient paradigm for expressing parallelism. This is particularly true for tools that automatically extract the data dependencies among the tasks while allowing to exploit ...

[Abstract] This paper presents RGen, a parallel data generator for benchmarking Big Data workloads, which integrates existing features and new functionalities in a standalone tool. The main functionalities developed in ...

[Abstract] The problem of generating complex synchronization patterns using automated tools is addressed in this paper. This work was originally motivated by the need of fast and jitter free synchronization in scientific ...

[Abstract] Due to the continuous development in the field of Next Generation Sequencing (NGS) technologies that have allowed researchers to take advantage of greater genetic samples in less time, it is a matter of relevance ...

[Abstract] Particle Swarm Optimization (PSO) is a popular population-based search algorithm that has been applied to all kinds of complex optimization problems. Although the performance of the algorithm strongly depends ...

[Abstract] Python has become one of the most used and taught languages nowadays. Its expressiveness, cross-compatibility and ease of use have made it popular in areas as diverse as finance, bioinformatics or machine ...

[Abstract]: The main objective of this work is to bring supercomputing and parallel processing closer to non-specialized audiences by building a Raspberry Pi cluster, called Clupiter, which emulates the operation of a ...

[Abstract]: The increasing success and scaling of Deep Learning models demands higher computational efficiency and power. Sparsification can lead to both smaller models as well as higher compute efficiency, and accelerated ...

[Abstract]: Java has been the backbone of Big Data processing for more than a decade due to its interesting features such as object orientation, cross-platform portability and good programming productivity. In fact, most ...