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Patrizio Dazzi

Patrizio Dazzi appears in the imported research catalog. Authorship, coauthor and topic links are available while profile ownership is still unclaimed.

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Distributed, Parallel, and Cluster ComputingNetworking and Internet ArchitectureArtificial IntelligenceMachine LearningProgramming LanguagesSocial and Information NetworksSoftware Engineering

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Published work

9 published item(s)

preprint2026arXiv

High-Performance Serverless Computing: A Systematic Literature Review on Serverless for HPC, AI, and Big Data

The widespread deployment of large-scale, compute-intensive applications such as high-performance computing, artificial intelligence, and big data is leading to convergence between cloud and high-performance computing infrastructures. Cloud providers are increasingly integrating high-performance computing capabilities in their infrastructures, such as hardware accelerators and high-speed interconnects, while researchers in the high-performance computing community are starting to explore cloud-native paradigms to improve scalability, elasticity, and resource utilization. In this context, serverless computing emerges as a promising execution model to efficiently handle highly dynamic, parallel, and distributed workloads. This paper presents a comprehensive systematic literature review of 122 research articles published between 2018 and early 2025, exploring the use of the serverless paradigm to develop, deploy, and orchestrate compute-intensive applications across cloud, high-performance computing, and hybrid environments. From these, a taxonomy comprising eight primary research directions and nine targeted use case domains is proposed, alongside an analysis of recent publication trends and collaboration networks among authors, highlighting the growing interest and interconnections within this emerging research field. Overall, this work aims to offer a valuable foundation for both new researchers and experienced practitioners, guiding the development of next-generation serverless solutions for parallel compute-intensive applications.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Trade-offs in Decentralized Agentic AI Discovery Across the Compute Continuum

Agentic systems deployed across the compute continuum need discovery mechanisms that remain effective across cloud, edge, and intermittently connected domains. In some emerging agentic architectures, decentralized discovery is already an active design direction, placing DHT-based lookup on the path toward agent directories. This paper studies the trade-offs among major structured-overlay families for agent discovery, comparing Chord, Pastry, and Kademlia as candidate indexing substrates within a shared control-plane framework. Using a benchmark subset centered on a 4096-node stationary comparison and a representative 4096-node churn benchmark, the paper characterizes how discovery reliability, startup behavior, and control-plane overhead vary across these overlays. The goal is to clarify the operating points they expose for agent discovery across edge-to-cloud environments.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Challenges to be addressed for realising an Ephemeral Cloud Federation

This paper sketches the challenges to address to realise a support able to achieve an Ephemeral Cloud Federation, an innovative cloud computing paradigm that enables the exploitation of a dynamic, personalised and context-aware set of resources. The aim of the Ephemeral Federation is to answer to the need of combining private data-centres with both federation of cloud providers and the resource on the edge of the network. The goal of the Ephemeral Federation is to deliver a context-aware and personalised federations of computational, data and network resources, able to manage their heterogeneity in a highly distributed deployment, which can dynamically bring data and computation close to the final user.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

Epidemic Information Diffusion: A Simple Solution to Support Community-based Recommendations in P2P Overlays

Epidemic protocols proved to be very efficient solutions for supporting dynamic and complex information diffusion in highly dis- tributed computing infrastructures, like P2P environments. They are useful bricks for building and maintaining virtual network topologies, in the form of overlay networks as well as to support pervasive diffusion of information when it is injected into the network. This paper proposes a simple architecture exploiting the features of epidemic approaches to foster a collaborative percolation of information between computing nodes belonging to the network aimed at building a system that groups similar users and spread useful information among them.

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preprint2015arXiv

Tools and Models for High Level Parallel and Grid Programming

When algorithmic skeletons were first introduced by Cole in late 1980 the idea had an almost immediate success. The skeletal approach has been proved to be effective when application algorithms can be expressed in terms of skeletons composition. However, despite both their effectiveness and the progress made in skeletal systems design and implementation, algorithmic skeletons remain absent from mainstream practice. Cole and other researchers, focused the problem. They recognized the issues affecting skeletal systems and stated a set of principles that have to be tackled in order to make them more effective and to take skeletal programming into the parallel mainstream. In this thesis we propose tools and models for addressing some among the skeletal programming environments issues. We describe three novel approaches aimed at enhancing skeletons based systems from different angles. First, we present a model we conceived that allows algorithmic skeletons customization exploiting the macro data-flow abstraction. Then we present two results about the exploitation of meta-programming techniques for the run-time generation and optimization of macro data-flow graphs. In particular, we show how to generate and how to optimize macro data-flow graphs accordingly both to programmers provided non-functional requirements and to execution platform features. The last result we present are the Behavioural Skeletons, an approach aimed at addressing the limitations of skeletal programming environments when used for the development of component-based Grid applications. We validated all the approaches conducting several test, performed exploiting a set of tools we developed.

0 citations0 reviewsNo code linkedOpen access
preprint2013arXiv

A Tool for Programming Embarrassingly Task Parallel Applications on CoW and NoW

Embarrassingly parallel problems can be split in parts that are characterized by a really low (or sometime absent) exchange of information during their computation in parallel. As a consequence they can be effectively computed in parallel exploiting commodity hardware, hence without particularly sophisticated interconnection networks. Basically, this means Clusters, Networks of Workstations and Desktops as well as Computational Clouds. Despite the simplicity of this computational model, it can be exploited to compute a quite large range of problems. This paper describes JJPF, a tool for developing task parallel applications based on Java and Jini that showed to be an effective and efficient solution in environment like Clusters and Networks of Workstations and Desktops.

0 citations0 reviewsNo code linkedOpen access
preprint2013arXiv

ATLAAS-P2P: a two layer network solution for easing the resource discovery process in unstructured networks

ATLAAS-P2P is a two-layered P2P architecture for developing systems providing resource aggregation and approximated discovery in P2P networks. Such systems allow users to search the desired resources by specifying their requirements in a flexible and easy way. From the point of view of resource providers, this system makes available an effective solution supporting providers in being reached by resource requests.

0 citations0 reviewsNo code linkedOpen access
preprint2013arXiv

Let's Annotate to Let Our Code Run in Parallel

This paper presents an approach that exploits Java annotations to provide meta information needed to automatically transform plain Java programs into parallel code that can be run on multicore workstation. Programmers just need to decorate the methods that will eventually be executed in parallel with standard Java annotations. Annotations are automatically processed at launch-time and parallel byte code is derived. Once in execution the program automatically retrieves the information about the executing platform and evaluates the information specified inside the annotations to transform the byte-code into a semantically equivalent multithreaded version, depending on the target architecture features. The results returned by the annotated methods, when invoked, are futures with a wait-by-necessity semantics.

0 citations0 reviewsNo code linkedOpen access
preprint2011arXiv

On Democracy in Peer-to-Peer systems

The information flow inside a P2P network is highly dependent on the network structure. In order to ease the diffusion of relevant data toward interested peers, many P2P protocols gather similar nodes by putting them in direct contact. With this approach the similarity between nodes is computed in a point-to-point fashion: each peer individually identifies the nodes that share similar interests with it. This leads to the creation of a sort of "private" communities, limited to each peer neighbors list. This "private" knowledge do not allow to identify the features needed to discover and characterize the correlations that collect similar peers in broader groups. In order to let these correlations to emerge, the collective knowledge of peers must be exploited. One common problem to overcome in order to avoid the "private" vision of the network, is related to how distributively determine the representation of a community and how nodes may decide to belong to it. We propose to use a gossip-like approach in order to let peers elect and identify leaders of interest communities. Once leaders are elected, their profiles are used as community representatives. Peers decide to adhere to a community or another by choosing the most similar representative they know about.

0 citations0 reviewsNo code linkedOpen access