- ECTS Credits: 6
- Semester: 1
- Year: 2
- Campus: Ivan Franko National University of Lviv
- Language: English
- ECTS Credits: 14
- Year: 2
- Campus: Silesian University of Technology
- Language: English
- Additional info:
Students choose four courses (two for 4 ECTS and two for 3 ECTS) from among the offered courses. The courses offered will be updated each year.
The exemplary courses offer is given below:- Queuing theory,
- Finite groups,
- Optimization theory with applications,
- Inverse problems,
- Heuristic optimization methods,
- Computational Geometry,
- Graphs and Algorithms,
- Complexity Theory,
- Introduction to modern cryptography,
- AI Security,
- Differential geometry,
- Complex analysis
- Modelling with R,
- Program specialization and metaprogramming,
- Development of computer games.
- Unit Coordinator: Antonio Cicone
- ECTS Credits: 3
- Semester: 2
- Year: 1
- Campus: University of L'Aquila
- Language: English
- Aims:
Learning Objectives
The aim of this course is to provide the student with knowledge of
Parallel Computing and the ability to analyze theoretical properties and
design mathematical software for high-performance computation.Learning Outcomes
On successful completion of this module, the student should:
- have profound knowledge and understanding of the most relevant
numerical methods for numerical computation and the design of accurate
and highly performant mathematical software;
- demonstrate skills in choosing the most suitable numerical method to
be implemented depending on the problem to be solved. Furthermore,
they should demonstrate ability in developing mathematical software and
in providing its theoretical analysis;
- demonstrate the ability to read and understand other texts on related
topics. - Content:
NUMERICAL INTEGRATION
Quadrature Formulae, The Midpoint or Rectangle Formula, The
Trapezoidal Formula, The Cavalieri-Simpson Formula.
FOURIER TRANSFORM
Orthogonal Polynomials in Approximation Theory, Fourier Trigonometric
Polynomials, The Fast Fourier Transform.
NUMERICAL SOLUTION OF ORDINARY DIFFERENTIAL EQUATIONS
The Cauchy Problem, One-Step Numerical Methods, Analysis of One-Step Methods, The Zero-Stability, Convergence Analysis, The Absolute
Stability, Difference Equations, Runge-Kutta Methods, Derivation of an
Explicit RK Method, Systems of ODEs. - Pre-requisites:
Basic Numerical Analysis and Linear Algebra.
Contents - Reading list:
A. Quarteroni, R. Sacco, F. Saleri, P. Gervasio, Numerical Mathematics,
Springer (2014).
The book in pdf is available for all students of the University at
https://link-springer-com.univaq.clas.cineca.it/book/10.1007/978-0-387-22750-4
- Code: DT0506
- Unit Coordinator: Antonio Cicone
- ECTS Credits: 3
- Semester: 2
- Year: 1
- Campus: University of L'Aquila
- Language: English
- Aims:
Learning Objectives
The aim of this course is to provide the student with knowledge of
Parallel Computing and the ability to analyze theoretical properties and
design mathematical software for high-performance computation.Learning Outcomes
On successful completion of this module, the student should:
- have profound knowledge and understanding of the most relevant
numerical methods for numerical computation and the design of accurate
and highly performant mathematical software;
- demonstrate skills in choosing the most suitable numerical method to
be implemented depending on the problem to be solved. Furthermore,
they should demonstrate ability in developing mathematical software and
in providing its theoretical analysis;
- demonstrate the ability to read and understand other texts on related
topics. - Content:
Introduction to Parallel Computing
Motivation and Need for Parallel Computing
Types of Parallelism (Data, Task, and Instruction)
Parallel Architectures and Models
Parallel Programming Paradigms (e.g., Shared Memory, Distributed Memory)
Parallel Algorithms and Analysis
Parallel Performance Metrics and Analysis
Parallel Computing Platforms (e.g., Multicore CPUs, GPUs, Clusters)
Parallel Programming Languages and Libraries (e.g., OpenMP, MPI, CUDA)
Parallel Software Development Tools and Environments
Synchronization and Communication in Parallel Computing
Load Balancing Techniques in Parallel Computing
Parallel I/O and File Systems
Parallelism in Scientific Computing and Engineering Applications
Parallelism in Data Science and Big Data Analytics
Parallelism in Web and Cloud Computing
Parallelism in High-Performance Computing (HPC) and Supercomputing
Parallelism and Energy Efficiency
Parallelism and Scalability
Case Studies of Parallel Computing Applications - Pre-requisites:
Basic Numerical Analysis and Linear Algebra.
- Reading list:
A. Quarteroni, R. Sacco, F. Saleri, P. Gervasio, Numerical Mathematics,
Springer (2014).The book in pdf is available for all students of the University at
https://link-springer-com.univaq.clas.cineca.it/book/10.1007/978-0-387-22750-4
