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18 March 2024
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Last updated on
18 March 2024 |
Lecturer: Prof. Tommaso Cucinotta
Duration and format: 30 hours of front lessons (3 CFU)
Target programs: PhD in Artificial Intelligence, PhD in Data Science, PhD in Emerging Digital Technologies
Schedule: The course will begin on Thursday November 16th, 2023
Location: Aula 1 in the Sant'Anna site in Palazzo Toscanelli (close to the headquarters in P.zza Martiri). Students of the PhD in AI not based in Pisa will be able to attend via an on-line link provided to registered students.
Exam: Oral.
The upcoming lectures are scheduled as follows:
This course provides an overview of the challenges to face, and the technical solutions to embrace, when building large-scale, fault-tolerant, distributed and replicated real-time cloud services. These systems need to be capable of serving millions/billions of requests per second with industrial-grade reliability, availability and performance, and are composed of thousands of components spanning across millions of machines, worldwide. The course focuses on design, development and operations of scalable software systems, including big-data processing and analytics, as used increasingly often for nowadays intensive computations needed to train large machine-learning and artificial intelligence models, where the huge volumes of data to handle mandates the use of heavily distributed algorithms. The course covers also basic concepts on networking architectures for data-centre and cloud computing infrastructures.
Students need a basic understanding of software, computer architectures, distributed systems and communication protocols.
Students will acquire a unique insight into the world of cloud computing and big-data related technologies, and will be able to master key concepts behind them. This is a fundamental brick in the background of a software engineer / computer scientist who will deal with modern distributed software systems in industry or academia, spanning across high-performance, cloud and even (increasingly connected) embedded systems.
Prof. Tommaso Cucinotta has a MSc in Computer Engineering from University of Pisa and a PhD from Scuola Superiore Sant'Anna. He spent more than 10 years at the Real-Time Systems Laboratory (ReTiS) of Scuola Superiore Sant'Anna carrying out research in security and smart-card based authentication, adaptive deadline-based scheduling in the Linux kernel for embedded, soft real-time and multimedia applications, temporal isolation in virtualized cloud services and novel OS designs for massively parallel and distributed systems. He has been MTS at Bell Labs in Dublin, carrying out industrial research on security and confidentiality, and real-time performance of cloud systems, with a focus on Telco applications. He has also been a Software Development Engineer in AWS DataBase Services in Dublin, Ireland, working on scalability and performance enhancements to the AWS DynamoDB NoSQL real-time data-base. Since 2016, he is back at the ReTiS of Scuola Superiore Sant'Anna as associate professor. He is a member of the PhD board of the Data Science PhD program jointly offered by Scuola Sant’Anna, University of Pisa, Scuola Normale Superiore, IMT Lucca and CNR since its first edition in the a.y. 2017/2018. He is also a member of the PhD board of the National PhD in AI - AI for Society - program jointly offered by Scuola Sant'Anna, University of Pisa and other academic institutions. Since year 2019, he is head of the real-time and embedded systems research area at the RETIS. Since October 2023, he is Associate Editor of the IEEE Transactions on Services Computing international magazine.
Download course brochure PDF format: CloudComputingBigData-2023-24.pdf
Access to course material: please, follow this link (reserved to attendees)
Access to course discussions: please, follow this link (reserved to attendees)
Follow-up course: Cloud Computing & Big Data Lab
Cloud Computing & Big Data 2022-23 Edition
Cloud Computing & Big Data 2021-22 Edition
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Last updated on
18 March 2024 |