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Advanced Computation
F3
2020 . 2021  - 1º semestre
SYNOPSIS SYLLABUS TIMETABLE ASSESSMENT SPECIFICATION


Specification sheet

Specific details
course codecycle os studiesacademic semestercredits ECTSteaching language
3005769116pt,en *)

*) N.B.  if there are students who do not speak Portuguese the language is English.

Learning goals
Recognize the importance and the application domains of advanced computing.
Know the main hardware and software components of a supercomputer.
Acquire knowledge and practice of parallel computing, including the use of directives/libraries for parallel computing and some specific algorithms for this kind of computing.
Gain experience in using advanced computing resources.

Competences:
Develop analysis and synthesis abilities;
Problem solving;
Usage of internet as communication means and source of information;
Decision-making capability;
Critical reasoning;
Capacity for autonomous learning;
Adaptability to new situations;
Research abilities.
Syllabus
Introduction to advanced computing systems: HPC vs. HTC.
Hardware architectures: clusters, MPP, hybrid architectures.
System software used in HPC: filesystems, libraries, resource management and job allocation. Trends in supercomputing.

Parallel computing and its importance. Main application domains. Paradigms of parallel computing: shared memory and distributed memory. Measuring the efficiency of parallel algorithms: speedup and Amdhal's law.

OpenMP programming: fork and join model. Parallel zone. Parallel loops, collective operations and barriers. Private and shared variables. Data race problems.

MPI. Parallelization techniques: data decomposition and domain decomposition. Model master-slave for data distribution and collection. MPI communication types. Collective operations for data and computation. Communicators and communication topologies. Creation of derived data types.
Applications to linear algebra problems and to the numerical solution of the Poisson equation.
Prerequisites
Programming experience with high level language (Fortran or C)
Generic skills to reach
. Competence in analysis and synthesis;
. Knowledge of a foreign language;
. Computer Skills for the scope of the study;
. Competence to solve problems;
. Critical thinking;
. Competence in autonomous learning;
. Research skills;
. Competence in organization and planning;
. Competence in oral and written communication;
. Competence in information management;
. Adaptability to new situations;
. Creativity;
(by decreasing order of importance)
Teaching hours per semester
lectures30
tutorial guidance15
total of teaching hours45

Assessment
Problem solving50 %
Project50 %

Bibliography of reference
Using MPI, 2nd Edition
William Gropp, Ewing Lusk and Anthony Skjellum, MIT Press

Using MPI-2
William Gropp, Ewing Lusk and Rajeev Thakur, MIT Press

Using OpenMP
Barbara Chapman, Gabriele Jost and Ruud van der Pas, MIT Press

Parallel Programming with MPI, P. Pacheco, Morgan Kaufmann Publishers, 1997.

Numerical Linear Algebra on High-Performance Computers
Jack J. Dongarra, Iain S. Duff , Danny C. Sorensen, Hank A. van der Vorst

The Sourcebook of Parallel Computing
Jack Dongarra , Geoffrey Fox , Ken Kennedy , Linda Torczon , William Gropp , Ian Foster (Editor), Andy White (Editor)

http://www.openmp.org

https://computing.llnl.gov/tutorials/mpi
Teaching method
Classes are essentially hands-on practice sessions of parallel computing.
Teaching involves slide presentations of theoretical material, programming examples, and programming exercises . Internet access is used for obtaining relevant material.

The programming exercises are made using a command line terminal in Windows/Linux/MacOS, GNU compilers and the mpich implementation of MPI. Access to a remote computer cluster is given for the problem assignments for evaluation.
Resources used

Acesso a computadores e a um sistema de computação avançada


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