Advanced Numerical Analysis II and Scientific Computing

Advanced Numerical Analysis II and Scientific Computing

The course Advanced Numerical Analysis II (Master Programme in Mathematics) is this year slightly modified with respect to previous academic years.
In fact, it is taught by Marco Caliari (elliptic and parabolic equations, finite elements methods) and Giacomo Albi
(hyperbolic equations, finite volumes methods, optimization methods), with a total of 40 theory hours and 12 laboratory
hours. In the laboratory hours basic implementations with FreeFem++ and Clawpack will be presented. More sophisticated
examples and techniques will be presented in the seminar course Scientific Computing, taught by Marco Caliari. Partially
based upon the interest of the students, it will cover one or more of the following topics:

Advanced examples with FreeFem++ (

Advanced examples with Clawpack (

BLAS libraries and optimized versions (ATLAS, openblas, MKL, ACML)

SuiteSparse library for sparse matrices (

Advanced examples in Matlab of Finite Differences approximations (multidimensiona, toeplitz, kron, sparse, ...),
with preconditioned sparse linear systems solvers (pcg, gmres, bicgstab, ..., ilu, ichol)

Spectral methods (FFT and NFFT

SageMath per analytical or arbitrary precision approximations (

Python for numerical analysis (scipy, numpy, ...)

Use of the new computational platform ( for high performance computing (HPC)

Optimization with CVX (

Due to its computational approach, Scientific Computing is recommended to students in Computer Science which wood like to
get in contact with the topics of Modelling, Simulation, and Optimization.

For any further information, please do not hesitate to contact me.

Marco Caliari
Publication date
Friday, February 9, 2018 - 1:18:37 PM
Last Modified
Friday, February 16, 2018- 11:38:51 AM
Advanced Numerical Analysis II and Scientific Computing
Published by
Marco Caliari
Advanced numerical analysis II (2017/2018)
Scientific computing (seminar course) (2017/2018)
Master's degree in Bioinformatics and Medical Biotechnology
Master's degree in Computer Science and Engineering
Master's degree in Mathematics