Learning objectives
The aim of the course is to define and characterize computing systems, focusing on parallel and distributed computing systems. A sound theoretical foundation will be developed, related to performance evaluation and programming models of complex computing systems. From a practical point of view, some important tools for parallel and distributed programming will be illustrated. The course will also illustrate the peer-to-peer paradigm and the principles of autonomic computing, as well as a design solution for adaptive peer-to-peer systems. The last part of the course will be related to the simulation of complex systems, in particular peer-to-peer and autonomic systems.
Prerequisites
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Course unit content
Systems e models
- State space
- Deterministic and stochastic models
- Complex systems
- Complex adaptive systems
- Population dynamics
- Network topologies
- DEVS models
Computing systems
- Information theory
- Taxonomy of computing systems
- Automata
- Von Neumann architecture
Parallel computing
- General concepts
- Parallel programming models
- Multicore systems, Cell, General Purpose GPU Programming
- NUMA architecture; Onyx2
- Massive parallelism, CM2
- Message Passing Interface (MPI)
Distributed computing
- Cluster computing
- Grid computing
- Cloud computing
Pervasive computing
Peer-to-Peer Systems
- State Variables
- Dynamics of peer-to-peer networks
- Design issues
- Design strategies
- Most important overlay schemes (Napster, BitTorrent, eMule, JXTA, Skype, Chord)
- Sip2Peer middleware
Autonomic Computing
- The four principles of autonomic computing
- Networked Autonomic Machine
- Adaptive Evolutionary Framework
Simulations
- General concepts about simulations
- Event oriented simulations
- DEUS: a tool for complex simulations
Practice with the Sip2Peer middleware.
Practice with the DEUS simulation tool.
Full programme
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Bibliography
1) C. Ghezzi, D. Mandrioli, "Informatica Teorica", Città Studi, 1989.
2) D. E. Culler, J. Pal Singh, “Parallel Computer Architecture: A Hardware/Software Approach”, Morgan Kaufman, 1999.
3) B.P. Zeighler, H. Praehofer, T.G. Kim, "Theory of Modeling and Simulation", Second Edition, Academic Press, 2000.
Teaching methods
Lectures.
Assessment methods and criteria
Written exam and small project.
Other information
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