Design and Performance Evaluation of Network-on-Chip Communication Protocols and Architectures

The scale down of transistor technology allows microelectronics manufacturers such as Intel and IBM to build always more sophisticated systems on a single microchip. The classical interconnection solutions based on shared buses or direct connections between the modules of the chip are becoming obsolete as they struggle to sustain the increasing tight bandwidth and latency constraints that these systems demand. The most promising solution for the future chip interconnects are the Networks on Chip (NoC). NoCs are network composed by routers and channels used to inter- connect the different components installed on the single microchip. Examples of advanced processors based on NoC interconnects are the IBM Cell processor, composed by eight CPUs that is installed on the Sony Playstation III and the Intel Teraflops pro ject composed by 80 independent (simple) microprocessors. On chip integration is becoming popular not only in the Chip Multi Processor (CMP) research area but also in the wider and more heterogeneous world of Systems on Chip (SoC). SoC comprehend all the electronic devices that surround us such as cell-phones, smart-phones, house embedded systems, automotive systems, set-top boxes etc... SoC manufacturers such as ST Microelectronics , Samsung, Philips and also Universities such as Bologna University, M.I.T., Berkeley and more are all proposing proprietary frameworks based on NoC interconnects. These frameworks help engineers in the switch of design methodology and speed up the development of new NoC-based systems on chip. In this Thesis we propose an introduction of CMP and SoC interconnection networks. Then focusing on SoC systems we propose: • a detailed analysis based on simulation of the Spidergon NoC, a ST Microelectronics solution for SoC interconnects. The Spidergon NoC differs from many classical solutions inherited from the parallel computing world. Here we propose a detailed analysis of this NoC topology and routing algorithms. Furthermore we propose aEqualized a new routing algorithm designed to optimize the use of the resources of the network while also increasing its performance; • a methodology flow based on modified publicly available tools that combined can be used to design, model and analyze any kind of System on Chip; • a detailed analysis of a ST Microelectronics-proprietary transport-level protocol that the author of this Thesis helped developing; • a simulation-based comprehensive comparison of different network interface designs proposed by the author and the researchers at AST lab, in order to integrate shared-memory and message-passing based components on a single System on Chip; • a powerful and flexible solution to address the time closure exception issue in the design of synchronous Networks on Chip. Our solution is based on relay stations repeaters and allows to reduce the power and area demands of NoC interconnects while also reducing its buffer needs; • a solution to simplify the design of the NoC by also increasing their performance and reducing their power and area consumption. We propose to replace complex and slow virtual channel-based routers with multiple and flexible small Multi Plane ones. This solution allows us to reduce the area and power dissipation of any NoC while also increasing its performance especially when the resources are reduced. This Thesis has been written in collaboration with the Advanced System Technology laboratory in Grenoble France, and the Computer Science Department at Columbia University in the city of New York.

Very Long Baseline Interferometry in Italy Wide-field VLBI imaging and astrometry and prospects for an Italian VLBI network including the Sardinia Radio Telescope

In this thesis the use of widefield imaging techniques and VLBI observations with a limited number of antennas are explored. I present techniques to efficiently and accurately image extremely large UV datasets. Very large VLBI datasets must be reduced into multiple, smaller datasets if today’s imaging algorithms are to be used to image them. I present a procedure for accurately shifting the phase centre of a visibility dataset. This procedure has been thoroughly tested and found to be almost two orders of magnitude more accurate than existing techniques. Errors have been found at the level of one part in 1.1 million. These are unlikely to be measurable except in the very largest UV datasets. Results of a four-station VLBI observation of a field containing multiple sources are presented. A 13 gigapixel image was constructed to search for sources across the entire primary beam of the array by generating over 700 smaller UV datasets. The source 1320+299A was detected and its astrometric position with respect to the calibrator J1329+3154 is presented. Various techniques for phase calibration and imaging across this field are explored including using the detected source as an in-beam calibrator and peeling of distant confusing sources from VLBI visibility datasets. A range of issues pertaining to wide-field VLBI have been explored including; parameterising the wide-field performance of VLBI arrays; estimating the sensitivity across the primary beam both for homogeneous and heterogeneous arrays; applying techniques such as mosaicing and primary beam correction to VLBI observations; quantifying the effects of time-average and bandwidth smearing; and calibration and imaging of wide-field VLBI datasets. The performance of a computer cluster at the Istituto di Radioastronomia in Bologna has been characterised with regard to its ability to correlate using the DiFX software correlator. Using existing software it was possible to characterise the network speed particularly for MPI applications. The capabilities of the DiFX software correlator, running on this cluster, were measured for a range of observation parameters and were shown to be commensurate with the generic performance parameters measured. The feasibility of an Italian VLBI array has been explored, with discussion of the infrastructure required, the performance of such an array, possible collaborations, and science which could be achieved. Results from a 22 GHz calibrator survey are also presented. 21 out of 33 sources were detected on a single baseline between two Italian antennas (Medicina to Noto). The results and discussions presented in this thesis suggest that wide-field VLBI is a technique whose time has finally come. Prospects for exciting new science are discussed in the final chapter.

Engineering Agent-Oriented Technologies and Programming Languages for Computer Programming and Software Development

Mainstream hardware is becoming parallel, heterogeneous, and distributed on every desk, every home and in every pocket. As a consequence, in the last years software is having an epochal turn toward concurrency, distribution, interaction which is pushed by the evolution of hardware architectures and the growing of network availability. This calls for introducing further abstraction layers on top of those provided by classical mainstream programming paradigms, to tackle more effectively the new complexities that developers have to face in everyday programming. A convergence it is recognizable in the mainstream toward the adoption of the actor paradigm as a mean to unite object-oriented programming and concurrency. Nevertheless, we argue that the actor paradigm can only be considered a good starting point to provide a more comprehensive response to such a fundamental and radical change in software development. Accordingly, the main objective of this thesis is to propose Agent-Oriented Programming (AOP) as a high-level general purpose programming paradigm, natural evolution of actors and objects, introducing a further level of human-inspired concepts for programming software systems, meant to simplify the design and programming of concurrent, distributed, reactive/interactive programs. To this end, in the dissertation first we construct the required background by studying the state-of-the-art of both actor-oriented and agent-oriented programming, and then we focus on the engineering of integrated programming technologies for developing agent-based systems in their classical application domains: artificial intelligence and distributed artificial intelligence. Then, we shift the perspective moving from the development of intelligent software systems, toward general purpose software development. Using the expertise maturated during the phase of background construction, we introduce a general-purpose programming language named simpAL, which founds its roots on general principles and practices of software development, and at the same time provides an agent-oriented level of abstraction for the engineering of general purpose software systems.

Applications of network-based approaches in drug research

Recent research trends in computer-aided drug design have shown an increasing interest towards the implementation of advanced approaches able to deal with large amount of data. This demand arose from the awareness of the complexity of biological systems and from the availability of data provided by high-throughput technologies. As a consequence, drug research has embraced this paradigm shift exploiting approaches such as that based on networks. Indeed, the process of drug discovery can benefit from the implementation of network-based methods at different steps from target identification to drug repurposing. From this broad range of opportunities, this thesis is focused on three main topics: (i) chemical space networks (CSNs), which are designed to represent and characterize bioactive compound data sets; (ii) drug-target interactions (DTIs) prediction through a network-based algorithm that predicts missing links; (iii) COVID-19 drug research which was explored implementing COVIDrugNet, a network-based tool for COVID-19 related drugs. The main highlight emerged from this thesis is that network-based approaches can be considered useful methodologies to tackle different issues in drug research. In detail, CSNs are valuable coordinate-free, graphically accessible representations of structure-activity relationships of bioactive compounds data sets especially for medium-large libraries of molecules. DTIs prediction through the random walk with restart algorithm on heterogeneous networks can be a helpful method for target identification. COVIDrugNet is an example of the usefulness of network-based approaches for studying drugs related to a specific condition, i.e., COVID-19, and the same ‘systems-based’ approaches can be used for other diseases. To conclude, network-based tools are proving to be suitable in many applications in drug research and provide the opportunity to model and analyze diverse drug-related data sets, even large ones, also integrating different multi-domain information.

What do rendering options tell us about the translating mind? Testing the choice network analysis hypothesis

Frame. Assessing the difficulty of source texts and parts thereof is important in CTIS, whether for research comparability, for didactic purposes or setting price differences in the market. In order to empirically measure it, Campbell & Hale (1999) and Campbell (2000) developed the Choice Network Analysis (CNA) framework. Basically, the CNA’s main hypothesis is that the more translation options (a group of) translators have to render a given source text stretch, the higher the difficulty of that text stretch will be. We will call this the CNA hypothesis. In a nutshell, this research project puts the CNA hypothesis to the test and studies whether it does actually measure difficulty. Data collection. Two groups of participants (n=29) of different profiles and from two universities in different countries had three translation tasks keylogged with Inputlog, and filled pre- and post-translation questionnaires. Participants translated from English (L2) into their L1s (Spanish or Italian), and worked—first in class and then at home—using their own computers, on texts ca. 800–1000 words long. Each text was translated in approximately equal halves in two 1-hour sessions, in three consecutive weeks. Only the parts translated at home were considered in the study. Results. A very different picture emerged from data than that which the CNA hypothesis might predict: there was no prevalence of disfluent task segments when there were many translation options, nor was a prevalence of fluent task segments associated to fewer translation options. Indeed, there was no correlation between the number of translation options (many and few) and behavioral fluency. Additionally, there was no correlation between pauses and both behavioral fluency and typing speed. The discussed theoretical flaws and the empirical evidence lead to the conclusion that the CNA framework does not and cannot measure text and translation difficulty.

An architecture for network acceleration as a service in the cloud continuum

The pervasive availability of connected devices in any industrial and societal sector is pushing for an evolution of the well-established cloud computing model. The emerging paradigm of the cloud continuum embraces this decentralization trend and envisions virtualized computing resources physically located between traditional datacenters and data sources. By totally or partially executing closer to the network edge, applications can have quicker reactions to events, thus enabling advanced forms of automation and intelligence. However, these applications also induce new data-intensive workloads with low-latency constraints that require the adoption of specialized resources, such as high-performance communication options (e.g., RDMA, DPDK, XDP, etc.). Unfortunately, cloud providers still struggle to integrate these options into their infrastructures. That risks undermining the principle of generality that underlies the cloud computing scale economy by forcing developers to tailor their code to low-level APIs, non-standard programming models, and static execution environments. This thesis proposes a novel system architecture to empower cloud platforms across the whole cloud continuum with Network Acceleration as a Service (NAaaS). To provide commodity yet efficient access to acceleration, this architecture defines a layer of agnostic high-performance I/O APIs, exposed to applications and clearly separated from the heterogeneous protocols, interfaces, and hardware devices that implement it. A novel system component embodies this decoupling by offering a set of agnostic OS features to applications: memory management for zero-copy transfers, asynchronous I/O processing, and efficient packet scheduling. This thesis also explores the design space of the possible implementations of this architecture by proposing two reference middleware systems and by adopting them to support interactive use cases in the cloud continuum: a serverless platform and an Industry 4.0 scenario. A detailed discussion and a thorough performance evaluation demonstrate that the proposed architecture is suitable to enable the easy-to-use, flexible integration of modern network acceleration into next-generation cloud platforms.