Actas da 10ª Conferência sobre Redes de Computadores

Universidade do MinhoCCTCCentro AlgoritmiCisco SystemsIEEE Portugal Sectio

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

Hierarchical Strategies for Fault-Tolerance in Reconfigurable Architectures

This thesis presents a novel hierarchical fault-tolerance methodology for fault recovery in reconfigurable devices. As the semiconductor industry moves to producing ever smaller transistors, the number of faults occurring increases. At current technology nodes, unavoidable variations in production cause transistor devices to perform outside of ideal ranges. This variability manifests as faults at higher levels and has a knock-on effect for yields. In some ways, fault tolerance has never been more important. To better explore the area of variability, a novel reconfigurable architecture was designed: Programmable Analogue and Digital Array (PAnDA). By allowing reconfiguration from the transistor level to the logic block level, PAnDA allows for design space exploration, previously only available through simulation, in hardware. The main advantage of this is that design modifications can be tested almost instantaneously, as opposed to running time consuming transistor-level simulations. As a result of this design, each level of PAnDA’s configuration contains structural homogeneity, allowing multiple implementations of the same circuit on the same hardware. This potentially creates opportunities for fault tolerance through reconfiguration, and so experimental work is performed to discover how best to utilise these properties of PAnDA. The findings show that it is possible to optimise the reconfiguration in the event of a fault, even if the nature and location of the fault are unknown

A Polyhedral Study of Mixed 0-1 Set

We consider a variant of the well-known single node fixed charge network flow set with constant capacities. This set arises from the relaxation of more general mixed integer sets such as lot-sizing problems with multiple suppliers. We provide a complete polyhedral characterization of the convex hull of the given set