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Università della Svizzera italiana

Predicting failures in complex multi-tier systems

Xin, Rui ; Pezzè, Mauro (Dir.)

Thèse de doctorat : Università della Svizzera italiana, 2020 ; 2020INFO017.

Complex multi-tier systems are composed of many distributed machines, feature multi-layer architecture and offer different types of services. Shared complex multi-tier systems, such as cloud systems, reduce costs and improves resource utilization efficiency, with a considerable amount of complexity and dynamics that challenge the reliability of the system. The new challenges of complex...

Università della Svizzera italiana

Less is more : efficient hardware design through Approximate Logic Synthesis

Scarabottolo, Ilaria ; Pozzi, Laura (Dir.)

Thèse de doctorat : Università della Svizzera italiana, 2020 ; 2020INFO023.

As energy efficiency becomes a crucial concern in almost every kind of digital application, Approximate Computing gains popularity as a potential answer to this ever-growing energy quest. Approximate Computing is a design paradigm particularly suited for error- resilient applications, where small losses in accuracy do not represent a significant reduction in the quality of the result. In these...

Université de Fribourg

Neuralink and Beyond: Challenges of Creating an Enhanced Human

Gurtner, Dimitri

(Internal working papers DIUF ; 21-01)

This article is a literature review of Neuralink, brain-machine interfaces (BMIs) and their applications, followed by future possibilities of BMIs and their potential impacts. Currently, BMIs predominantly have therapeutic applications, such as helping people with spinal cord injury by allowing them to control a computer directly with their brain. However, BMIs can also improve learning,...

Università della Svizzera italiana

Space-time multilevel Monte Carlo methods and their application to cardiac electrophysiology

Ben Bader, Seif ; Benedusi, Pietro ; Quaglino, Alessio ; Zulian, Patrick ; Krause, Rolf

In: Journal of computational physics, 2021, vol. 433, p. 17 p

We present a novel approach aimed at high-performance uncertainty quantification for time-dependent problems governed by partial differential equations. In particular, we consider input uncertainties described by a Karhunen-Loève expansion and compute statistics of high-dimensional quantities-of-interest, such as the cardiac activation potential. Our methodology relies on a close integration...

Università della Svizzera italiana

Scaling blockchains

Fynn, Enrique ; Pedone, Fernando (Dir.)

Thèse de doctorat : Università della Svizzera italiana, 2021 ; 2021INFO003.

Blockchains are a new type of state machine replication that have raised interesting challenges. A replicated state machine (RSM) is a well-established approach to building fault-tolerant systems. Because each replica needs to execute the same set of instructions to transition through the same state changes, adding more replicas does not translate directly to an increase in performance. On top...

Università della Svizzera italiana

Declarative performance testing automation : automating performance testing for the DevOps era

Ferme, Vincenzo ; Pautasso, Cesare (Dir.)

Thèse de doctorat : Università della Svizzera italiana, 2021 ; 2021INFO002.

Recent trends in industry show increasing adoption of Development and Operations (DevOps) practices. Reasons for increasing DevOps adoption are the focus on the creation of cross-functional teams, and the ability to release high-quality software at a fast pace. Alongside the adoption of DevOps, performance testing continues to evolve to meet the growing demands of the modern enterprise and its...

Università della Svizzera italiana

Multilevel minimization in trust-region framework : algorithmic and software developments

Kopaničáková, Alena ; Krause, Rolf (Dir.)

Thèse de doctorat : Università della Svizzera italiana, 2020 ; 2020INFO021.

The field of scientific computing is associated with the modeling of complex physical phenomena. The resulting numerical models are often described by differential equations, which, in many cases, can be related to non-convex minimization problems. Thus, after discretization, the solution of large-scale non-convex optimization problem is required. Various iterative solution strategies can be...

Università della Svizzera italiana

RESTalk : a visual and textual DSL for modelling RESTful conversations

Ivanchikj, Ana ; Pautasso, Cesare (Dir.)

Thèse de doctorat : Università della Svizzera italiana, 2021 ; 2021INFO001.

Digitalization is all around us, even more so in pandemic times where substantial part of our lives has been moved online. One of the key enablers of digitalization are the Application Programming Interfaces (APIs) which enable the communication and exchange of data between different systems. They abstract from the implementation details of the underlying systems and allow for the monetization...

Università della Svizzera italiana

Advanced metaheuristics for the probabilistic orienteering problem

Chou, Xiaochen ; Gambardella, Luca Maria (Dir.) ; Montemanni, Roberto (Codir.)

Thèse de doctorat : Università della Svizzera italiana, 2020 ; 2020INFO020.

Stochastic Optimization Problems take uncertainty into account. For this reason they are in general more realistic than deterministic ones, meanwhile, more difficult to solve. The challenge is both on modelling and computation aspects: exact methods usually work only for small instances, besides, there are several problems with no closed-form expression or hard- to-compute objective functions....

Università della Svizzera italiana

Learning structured neural representations for visual reasoning tasks

van Steenkiste, Sjoerd ; Schmidhuber, Jürgen (Dir.)

Thèse de doctorat : Università della Svizzera italiana, 2020 ; 2020INFO019.

Deep neural networks learn representations of data to facilitate problem-solving in their respective domains. However, they struggle to acquire a structured representation based on more symbolic entities, which are commonly understood as core abstractions central to human capacity for generalization. This dissertation studies this issue for visual reasoning tasks. Inspired by how humans solve...