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Intensive Computation - Calcolo Intensivo

Annalisa Massini

Office Hours: appointment by email
Aim of the course

The aim of the course is to provide students with methodologies for the solution of problems requiring intensive computation, in particular scientific problems.

Topics covered in this course include:

  • Introduction to Matlab
  • Concepts and methods: sparse matrices, eigenvalues and eigenvectors, linear algebras methods, etc.
  • Errors and simulations
  • Problems like Molecular Dynamics, Graph connectivity, Global search algorithms, etc.
  • Advanced topics on architectures and arithmetic operations
  • Introduction to GPU architecture and programming
  • Performance measures

Lectures 2018-2019

Lecture 1, February 27th, 2019 Introduction to the course - Lecture 1 - Introduction

Lecture 2, March 1st, 2019 Introduction to Matlab - Part 1 - Lecture 2 - Matlab
Laboratory, March 1st, 2019 Laboratory: Introductory exercises - Part 1

Lecture 3, March 6th, 2019 Introduction to Matlab - Part 2 - Lecture 3 - Matlab
Laboratory, March 6th, 2019 Laboratory: Introductory exercises - Part 2

Lecture 4, March 8th, 2019 Compact storage methods for sparse matrix: Coordinate, Compact Sparse Row CSR, Compact Sparse Column CSC and Modified Sparse Row MSR, Block Sparse Row, Skyline, Diagonal, Ellpack-Itpack. Lecture 4 - Sparse Matrices

  • Appendix of book Solving Numerical PDEs: Problems, Applications, Exercises - Formaggia, Saleri, Veneziani - 2012 - read pp. 395-409

Lecture 5, March 13th, 2019 Lecture by Dr. Viviana Arrigoni. Linear systems. Gaussian elimination for solving systems of linear equations. Pivoting. Methods to avoid pivoting. Random Butterfly Transformations and Positive definite methods Lecture 5 - Linear Systems Part 1

Lecture 6, March 15th, 2019 Lecture by Dr. Viviana Arrigoni. Linear systems. Cholesky factorization. Jacobi iterative method. Gauss-Seidel iterative method. Lecture 6 - Linear Systems Part 2

Lecture 7, March 20st, 2019 Discussion on exercises of Homework 1 and laboratory.


Some papers proposed for past exam projects - Articoli proposti per esami passati

Past year lectures

Exam

The exam consists of two parts:

  • Written exam. Students attending the lessons can take a mid-term exam and a final exam (or a whole exam). Mid-term and final exam (or whole exam) consist in a written test and exercises.
  • One of the following, at the choice of the student: oral exam/presentation of one-two papers/project.

There will also be homework assignments. Homeworks will contribute to the final grade.


Text of exams


Textbooks - Testi di riferimento

  • Introduction to High-Performance Scientific Computing, Lloyd D. Fosdick, Elizabeth R. Jessup, Carolyn J. C. Schauble and Gitta Domik, The MIT Press, 1996, ISBN 0-262-06181-3
  • Programming Massively Parallel Processors: A Hands-on Approach, David B. Kirk and Wen-mei W. Hwu, Morgan Kaufmann, 2010
  • Introduction to scientific computing: A Matrix-Vector Approach Using MATLAB, Charles F. Van Loan, Prentice Hall , 1997
  • Manuale di MATLAB. Consultare il sito: http://www.mathworks.com/help/techdoc/learn_matlab/bqr_2pl.html
  • Matlab. Concetti e progetti, Giovanni Naldi e Lorenzo Pareschi, Apogeo, 2007
  • Calcolo Scientifico: Esercizi e Problemi Risolti Con MATLAB e Octave, Alfio Quarteroni, Fausto Saleri, 2008

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-- AnnalisaMassini

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