Applications of High Speed Configurable Logic Devices in Modern Particle Physics Experiments

Several activities were conducted during my PhD activity. For the NEMO experiment a collaboration between the INFN/University groups of Catania and Bologna led to the development and production of a mixed signal acquisition board for the Nemo Km3 telescope. The research concerned the feasibility study for a different acquisition technique quite far from that adopted in the NEMO Phase 1 telescope. The DAQ board that we realized exploits the LIRA06 front-end chip for the analog acquisition of anodic an dynodic sources of a PMT (Photo-Multiplier Tube). The low-power analog acquisition allows to sample contemporaneously multiple channels of the PMT at different gain factors in order to increase the signal response linearity over a wider dynamic range. Also the auto triggering and self-event-classification features help to improve the acquisition performance and the knowledge on the neutrino event. A fully functional interface towards the first level data concentrator, the Floor Control Module, has been integrated as well on the board, and a specific firmware has been realized to comply with the present communication protocols. This stage of the project foresees the use of an FPGA, a high speed configurable device, to provide the board with a flexible digital logic control core. After the validation of the whole front-end architecture this feature would be probably integrated in a common mixed-signal ASIC (Application Specific Integrated Circuit). The volatile nature of the configuration memory of the FPGA implied the integration of a flash ISP (In System Programming) memory and a smart architecture for a safe remote reconfiguration of it. All the integrated features of the board have been tested. At the Catania laboratory the behavior of the LIRA chip has been investigated in the digital environment of the DAQ board and we succeeded in driving the acquisition with the FPGA. The PMT pulses generated with an arbitrary waveform generator were correctly triggered and acquired by the analog chip, and successively they were digitized by the on board ADC under the supervision of the FPGA. For the communication towards the data concentrator a test bench has been realized in Bologna where, thanks to a lending of the Roma University and INFN, a full readout chain equivalent to that present in the NEMO phase-1 was installed. These tests showed a good behavior of the digital electronic that was able to receive and to execute command imparted by the PC console and to answer back with a reply. The remotely configurable logic behaved well too and demonstrated, at least in principle, the validity of this technique. A new prototype board is now under development at the Catania laboratory as an evolution of the one described above. This board is going to be deployed within the NEMO Phase-2 tower in one of its floors dedicated to new front-end proposals. This board will integrate a new analog acquisition chip called SAS (Smart Auto-triggering Sampler) introducing thus a new analog front-end but inheriting most of the digital logic present in the current DAQ board discussed in this thesis. For what concern the activity on high-resolution vertex detectors, I worked within the SLIM5 collaboration for the characterization of a MAPS (Monolithic Active Pixel Sensor) device called APSEL-4D. The mentioned chip is a matrix of 4096 active pixel sensors with deep N-well implantations meant for charge collection and to shield the analog electronics from digital noise. The chip integrates the full-custom sensors matrix and the sparsifification/readout logic realized with standard-cells in STM CMOS technology 130 nm. For the chip characterization a test-beam has been set up on the 12 GeV PS (Proton Synchrotron) line facility at CERN of Geneva (CH). The collaboration prepared a silicon strip telescope and a DAQ system (hardware and software) for data acquisition and control of the telescope that allowed to store about 90 million events in 7 equivalent days of live-time of the beam. My activities concerned basically the realization of a firmware interface towards and from the MAPS chip in order to integrate it on the general DAQ system. Thereafter I worked on the DAQ software to implement on it a proper Slow Control interface of the APSEL4D. Several APSEL4D chips with different thinning have been tested during the test beam. Those with 100 and 300 um presented an overall efficiency of about 90% imparting a threshold of 450 electrons. The test-beam allowed to estimate also the resolution of the pixel sensor providing good results consistent with the pitch/sqrt(12) formula. The MAPS intrinsic resolution has been extracted from the width of the residual plot taking into account the multiple scattering effect.

A study on set variable representations in constraint programming

Il lavoro presentato in questa tesi si colloca nel contesto della programmazione con vincoli, un paradigma per modellare e risolvere problemi di ricerca combinatoria che richiedono di trovare soluzioni in presenza di vincoli. Una vasta parte di questi problemi trova naturale formulazione attraverso il linguaggio delle variabili insiemistiche. Dal momento che il dominio di tali variabili può essere esponenziale nel numero di elementi, una rappresentazione esplicita è spesso non praticabile. Recenti studi si sono quindi focalizzati nel trovare modi efficienti per rappresentare tali variabili. Pertanto si è soliti rappresentare questi domini mediante l'uso di approssimazioni definite tramite intervalli (d'ora in poi rappresentazioni), specificati da un limite inferiore e un limite superiore secondo un'appropriata relazione d'ordine. La recente evoluzione della ricerca sulla programmazione con vincoli sugli insiemi ha chiaramente indicato che la combinazione di diverse rappresentazioni permette di raggiungere prestazioni di ordini di grandezza superiori rispetto alle tradizionali tecniche di codifica. Numerose proposte sono state fatte volgendosi in questa direzione. Questi lavori si differenziano su come è mantenuta la coerenza tra le diverse rappresentazioni e su come i vincoli vengono propagati al fine di ridurre lo spazio di ricerca. Sfortunatamente non esiste alcun strumento formale per paragonare queste combinazioni. Il principale obiettivo di questo lavoro è quello di fornire tale strumento, nel quale definiamo precisamente la nozione di combinazione di rappresentazioni facendo emergere gli aspetti comuni che hanno caratterizzato i lavori precedenti. In particolare identifichiamo due tipi possibili di combinazioni, una forte ed una debole, definendo le nozioni di coerenza agli estremi sui vincoli e sincronizzazione tra rappresentazioni. Il nostro studio propone alcune interessanti intuizioni sulle combinazioni esistenti, evidenziandone i limiti e svelando alcune sorprese. Inoltre forniamo un'analisi di complessità della sincronizzazione tra minlex, una rappresentazione in grado di propagare in maniera ottimale vincoli lessicografici, e le principali rappresentazioni esistenti.

Implementation of a non ground meta interpreter for defeasible logic

Human reasoning is a fascinating and complex cognitive process that can be applied in different research areas such as philosophy, psychology, laws and financial. Unfortunately, developing supporting software (to those different areas) able to cope such as complex reasoning it’s difficult and requires a suitable logic abstract formalism. In this thesis we aim to develop a program, that has the job to evaluate a theory (a set of rules) w.r.t. a Goal, and provide some results such as “The Goal is derivable from the KB5 (of the theory)”. In order to achieve this goal we need to analyse different logics and choose the one that best meets our needs. In logic, usually, we try to determine if a given conclusion is logically implied by a set of assumptions T (theory). However, when we deal with programming logic we need an efficient algorithm in order to find such implications. In this work we use a logic rather similar to human logic. Indeed, human reasoning requires an extension of the first order logic able to reach a conclusion depending on not definitely true6 premises belonging to a incomplete set of knowledge. Thus, we implemented a defeasible logic7 framework able to manipulate defeasible rules. Defeasible logic is a non-monotonic logic designed for efficient defeasible reasoning by Nute (see Chapter 2). Those kind of applications are useful in laws area especially if they offer an implementation of an argumentation framework that provides a formal modelling of game. Roughly speaking, let the theory is the set of laws, a keyclaim is the conclusion that one of the party wants to prove (and the other one wants to defeat) and adding dynamic assertion of rules, namely, facts putted forward by the parties, then, we can play an argumentative challenge between two players and decide if the conclusion is provable or not depending on the different strategies performed by the players. Implementing a game model requires one more meta-interpreter able to evaluate the defeasible logic framework; indeed, according to Göedel theorem (see on page 127), we cannot evaluate the meaning of a language using the tools provided by the language itself, but we need a meta-language able to manipulate the object language8. Thus, rather than a simple meta-interpreter, we propose a Meta-level containing different Meta-evaluators. The former has been explained above, the second one is needed to perform the game model, and the last one will be used to change game execution and tree derivation strategies.

Multi-level models and infrastructures for simulating biological system development

The hierarchical organisation of biological systems plays a crucial role in the pattern formation of gene expression resulting from the morphogenetic processes, where autonomous internal dynamics of cells, as well as cell-to-cell interactions through membranes, are responsible for the emergent peculiar structures of the individual phenotype. Being able to reproduce the systems dynamics at different levels of such a hierarchy might be very useful for studying such a complex phenomenon of self-organisation. The idea is to model the phenomenon in terms of a large and dynamic network of compartments, where the interplay between inter-compartment and intra-compartment events determines the emergent behaviour resulting in the formation of spatial patterns. According to these premises the thesis proposes a review of the different approaches already developed in modelling developmental biology problems, as well as the main models and infrastructures available in literature for modelling biological systems, analysing their capabilities in tackling multi-compartment / multi-level models. The thesis then introduces a practical framework, MS-BioNET, for modelling and simulating these scenarios exploiting the potential of multi-level dynamics. This is based on (i) a computational model featuring networks of compartments and an enhanced model of chemical reaction addressing molecule transfer, (ii) a logic-oriented language to flexibly specify complex simulation scenarios, and (iii) a simulation engine based on the many-species/many-channels optimised version of Gillespie’s direct method. The thesis finally proposes the adoption of the agent-based model as an approach capable of capture multi-level dynamics. To overcome the problem of parameter tuning in the model, the simulators are supplied with a module for parameter optimisation. The task is defined as an optimisation problem over the parameter space in which the objective function to be minimised is the distance between the output of the simulator and a target one. The problem is tackled with a metaheuristic algorithm. As an example of application of the MS-BioNET framework and of the agent-based model, a model of the first stages of Drosophila Melanogaster development is realised. The model goal is to generate the early spatial pattern of gap gene expression. The correctness of the models is shown comparing the simulation results with real data of gene expression with spatial and temporal resolution, acquired in free on-line sources.

Hybrid constraint programming and metaheuristic methods for large scale optimization problems

This work presents hybrid Constraint Programming (CP) and metaheuristic methods for the solution of Large Scale Optimization Problems; it aims at integrating concepts and mechanisms from the metaheuristic methods to a CP-based tree search environment in order to exploit the advantages of both approaches. The modeling and solution of large scale combinatorial optimization problem is a topic which has arisen the interest of many researcherers in the Operations Research field; combinatorial optimization problems are widely spread in everyday life and the need of solving difficult problems is more and more urgent. Metaheuristic techniques have been developed in the last decades to effectively handle the approximate solution of combinatorial optimization problems; we will examine metaheuristics in detail, focusing on the common aspects of different techniques. Each metaheuristic approach possesses its own peculiarities in designing and guiding the solution process; our work aims at recognizing components which can be extracted from metaheuristic methods and re-used in different contexts. In particular we focus on the possibility of porting metaheuristic elements to constraint programming based environments, as constraint programming is able to deal with feasibility issues of optimization problems in a very effective manner. Moreover, CP offers a general paradigm which allows to easily model any type of problem and solve it with a problem-independent framework, differently from local search and metaheuristic methods which are highly problem specific. In this work we describe the implementation of the Local Branching framework, originally developed for Mixed Integer Programming, in a CP-based environment. Constraint programming specific features are used to ease the search process, still mantaining an absolute generality of the approach. We also propose a search strategy called Sliced Neighborhood Search, SNS, that iteratively explores slices of large neighborhoods of an incumbent solution by performing CP-based tree search and encloses concepts from metaheuristic techniques. SNS can be used as a stand alone search strategy, but it can alternatively be embedded in existing strategies as intensification and diversification mechanism. In particular we show its integration within the CP-based local branching. We provide an extensive experimental evaluation of the proposed approaches on instances of the Asymmetric Traveling Salesman Problem and of the Asymmetric Traveling Salesman Problem with Time Windows. The proposed approaches achieve good results on practical size problem, thus demonstrating the benefit of integrating metaheuristic concepts in CP-based frameworks.

Programming Robots with an Agent-Oriented BDI-based Control Architecture: Explorations using the JaCa and Webots Platforms

La crescente disponibilità di dispositivi meccanici e -soprattutto - elettronici le cui performance aumentano mentre il loro costo diminuisce, ha permesso al campo della robotica di compiere notevoli progressi. Tali progressi non sono stati fatti unicamente per ciò che riguarda la robotica per uso industriale, nelle catene di montaggio per esempio, ma anche per quella branca della robotica che comprende i robot autonomi domestici. Questi sistemi autonomi stanno diventando, per i suddetti motivi, sempre più pervasivi, ovvero sono immersi nello stesso ambiente nel quale vivono gli essere umani, e interagiscono con questi in maniera proattiva. Essi stanno compiendo quindi lo stesso percorso che hanno attraversato i personal computer all'incirca 30 anni fa, passando dall'essere costosi ed ingombranti mainframe a disposizione unicamente di enti di ricerca ed università, ad essere presenti all'interno di ogni abitazione, per un utilizzo non solo professionale ma anche di assistenza alle attività quotidiane o anche di intrattenimento. Per questi motivi la robotica è un campo dell'Information Technology che interessa sempre più tutti i tipi di programmatori software. Questa tesi analizza per prima cosa gli aspetti salienti della programmazione di controllori per robot autonomi (ovvero senza essere guidati da un utente), quindi, come l'approccio basato su agenti sia appropriato per la programmazione di questi sistemi. In particolare si mostrerà come un approccio ad agenti, utilizzando il linguaggio di programmazione Jason e quindi l'architettura BDI, sia una scelta significativa, dal momento che il modello sottostante a questo tipo di linguaggio è basato sul ragionamento pratico degli esseri umani (Human Practical Reasoning) e quindi è adatto alla implementazione di sistemi che agiscono in maniera autonoma. Dato che le possibilità di utilizzare un vero e proprio sistema autonomo per poter testare i controllori sono ridotte, per motivi pratici, economici e temporali, mostreremo come è facile e performante arrivare in maniera rapida ad un primo prototipo del robot tramite l'utilizzo del simulatore commerciale Webots. Il contributo portato da questa tesi include la possibilità di poter programmare un robot in maniera modulare e rapida per mezzo di poche linee di codice, in modo tale che l'aumento delle funzionalità di questo risulti un collo di bottiglia, come si verifica nella programmazione di questi sistemi tramite i classici linguaggi di programmazione imperativi. L'organizzazione di questa tesi prevede un capitolo di background nel quale vengono riportare le basi della robotica, della sua programmazione e degli strumenti atti allo scopo, un capitolo che riporta le nozioni di programmazione ad agenti, tramite il linguaggio Jason -quindi l'architettura BDI - e perché tale approccio è adatto alla programmazione di sistemi di controllo per la robotica. Successivamente viene presentata quella che è la struttura completa del nostro ambiente di lavoro software che comprende l'ambiente ad agenti e il simulatore, quindi nel successivo capitolo vengono mostrate quelle che sono le esplorazioni effettuate utilizzando Jason e un approccio classico (per mezzo di linguaggi classici), attraverso diversi casi di studio di crescente complessità; dopodiché, verrà effettuata una valutazione tra i due approcci analizzando i problemi e i vantaggi che comportano questi. Infine, la tesi terminerà con un capitolo di conclusioni e di riflessioni sulle possibili estensioni e lavori futuri.

Theoretical and Experimental Analysis of micro-CHP Energy Systems

In the framework of the micro-CHP (Combined Heat and Power) energy systems and the Distributed Generation (GD) concept, an Integrated Energy System (IES) able to meet the energy and thermal requirements of specific users, using different types of fuel to feed several micro-CHP energy sources, with the integration of electric generators of renewable energy sources (RES), electrical and thermal storage systems and the control system was conceived and built. A 5 kWel Polymer Electrolyte Membrane Fuel Cell (PEMFC) has been studied. Using experimental data obtained from various measurement campaign, the electrical and CHP PEMFC system performance have been determinate. The analysis of the effect of the water management of the anodic exhaust at variable FC loads has been carried out, and the purge process programming logic was optimized, leading also to the determination of the optimal flooding times by varying the AC FC power delivered by the cell. Furthermore, the degradation mechanisms of the PEMFC system, in particular due to the flooding of the anodic side, have been assessed using an algorithm that considers the FC like a black box, and it is able to determine the amount of not-reacted H2 and, therefore, the causes which produce that. Using experimental data that cover a two-year time span, the ageing suffered by the FC system has been tested and analyzed.

Portfolio Approaches in Constraint Programming

Recent research has shown that the performance of a single, arbitrarily efficient algorithm can be significantly outperformed by using a portfolio of —possibly on-average slower— algorithms. Within the Constraint Programming (CP) context, a portfolio solver can be seen as a particular constraint solver that exploits the synergy between the constituent solvers of its portfolio for predicting which is (or which are) the best solver(s) to run for solving a new, unseen instance. In this thesis we examine the benefits of portfolio solvers in CP. Despite portfolio approaches have been extensively studied for Boolean Satisfiability (SAT) problems, in the more general CP field these techniques have been only marginally studied and used. We conducted this work through the investigation, the analysis and the construction of several portfolio approaches for solving both satisfaction and optimization problems. We focused in particular on sequential approaches, i.e., single-threaded portfolio solvers always running on the same core. We started from a first empirical evaluation on portfolio approaches for solving Constraint Satisfaction Problems (CSPs), and then we improved on it by introducing new data, solvers, features, algorithms, and tools. Afterwards, we addressed the more general Constraint Optimization Problems (COPs) by implementing and testing a number of models for dealing with COP portfolio solvers. Finally, we have come full circle by developing sunny-cp: a sequential CP portfolio solver that turned out to be competitive also in the MiniZinc Challenge, the reference competition for CP solvers.

New integer programming models for balanced multi-country kep

Le persone che soffrono di insufficienza renale terminale hanno due possibili trattamenti da affrontare: la dialisi oppure il trapianto di organo. Nel caso volessero seguire la seconda strada, oltre che essere inseriti nella lista d'attesa dei donatori deceduti, possono trovare una persona, come il coniuge, un parente o un amico, disposta a donare il proprio rene. Tuttavia, non sempre il trapianto è fattibile: donatore e ricevente possono, infatti, presentare delle incompatibilità a livello di gruppo sanguigno o di tessuto organico. Come risposta a questo tipo di problema nasce il KEP (Kidney Exchange Program), un programma, ampiamente avviato in diverse realtà europee e mondiali, che si occupa di raggruppare in un unico insieme le coppie donatore/ricevente in questa stessa situazione al fine di operare e massimizzare scambi incrociati di reni fra coppie compatibili. Questa tesi approffondisce tale questione andando a valutare la possibilità di unire in un unico insieme internazionale coppie donatore/ricevente provenienti da più paesi. Lo scopo, naturalmente, è quello di poter ottenere un numero sempre maggiore di trapianti effettuati. Lo studio affronta dal punto di vista matematico problematiche legate a tale collaborazione: i paesi che eventualmente accettassero di partecipare a un simile programma, infatti, devono avere la garanzia non solo di ricavarne un vantaggio, ma anche che tale vantaggio sia equamente distribuito fra tutti i paesi partecipanti.

Groupme: city data and multi-preference activity allocation

Classic group recommender systems focus on providing suggestions for a fixed group of people. Our work tries to give an inside look at design- ing a new recommender system that is capable of making suggestions for a sequence of activities, dividing people in subgroups, in order to boost over- all group satisfaction. However, this idea increases problem complexity in more dimensions and creates great challenge to the algorithm’s performance. To understand the e↵ectiveness, due to the enhanced complexity and pre- cise problem solving, we implemented an experimental system from data collected from a variety of web services concerning the city of Paris. The sys- tem recommends activities to a group of users from two di↵erent approaches: Local Search and Constraint Programming. The general results show that the number of subgroups can significantly influence the Constraint Program- ming Approaches’s computational time and e�cacy. Generally, Local Search can find results much quicker than Constraint Programming. Over a lengthy period of time, Local Search performs better than Constraint Programming, with similar final results.

DESIGN AND IMPLEMENT DYNAMIC PROGRAMMING BASED DISCRETE POWER LEVEL SMART HOME SCHEDULING USING FPGA

With the development and capabilities of the Smart Home system, people today are entering an era in which household appliances are no longer just controlled by people, but also operated by a Smart System. This results in a more efficient, convenient, comfortable, and environmentally friendly living environment. A critical part of the Smart Home system is Home Automation, which means that there is a Micro-Controller Unit (MCU) to control all the household appliances and schedule their operating times. This reduces electricity bills by shifting amounts of power consumption from the on-peak hour consumption to the off-peak hour consumption, in terms of different “hour price”. In this paper, we propose an algorithm for scheduling multi-user power consumption and implement it on an FPGA board, using it as the MCU. This algorithm for discrete power level tasks scheduling is based on dynamic programming, which could find a scheduling solution close to the optimal one. We chose FPGA as our system’s controller because FPGA has low complexity, parallel processing capability, a large amount of I/O interface for further development and is programmable on both software and hardware. In conclusion, it costs little time running on FPGA board and the solution obtained is good enough for the consumers.