Portale della Didattica

HPC (High Performance Computing)

01HEKUU

A.A. 2024/25

Course Language

Inglese

Degree programme(s)

Master of science-level of the Bologna process in Quantum Engineering - Torino

Course structure

Teaching	Hours
Lezioni	51
Esercitazioni in laboratorio	9

Lecturers

Teacher	Status	SSD	h.Les	h.Ex	h.Lab	h.Tut	Years teaching
Sanchez Sanchez Edgar Ernesto	Professore Associato	IINF-05/A	51	0	0	0	2

Co-lectures

Espandi

Teacher	Status	SSD	h.Les	h.Ex	h.Lab	h.Tut
Rodriguez Condia Josie Esteban	Ricercatore L240/10	IINF-05/A	0	0	9	0

Context

SSD	CFU	Activities	Area context
ING-INF/05	6	B - Caratterizzanti	Ingegneria elettronica

Statistiche superamento esami

Anno accademico di inizio validit�

2024/25

Presentazione
Course description

The High Performance Computing (HPC) course is a mandatory course belonging to the Master Degree in Quantum Engineering, and it is taught in the second semester of the first year, and it is taught in English. The main goal of the course is to provide the students with a base knowledge of the traditional microprocessors, emphasizing the concepts related to multicore systems and High Performance Computing. During the course, the foundation concepts about HPC, and some of the most popular techniques for programming and use HPC are developed.

The High Performance Computing (HPC) course is a mandatory course belonging to the Master Degree in Quantum Engineering, and it is taught in the second semester of the first year, and it is taught in English. The main goal of the course is to provide the students with a base knowledge of the microprocessor cores, emphasizing the concepts related to multicore systems and High Performance Computing. During the course, the foundation concepts about HPC, and some of the most popular techniques for programming and use HPC are developed.

Risultati attesi
Expected Learning Outcomes

- Knowledge in computer architecture concepts - Knowledge in multiprocessor systems - Knowledge of the main elements composing a High Performance Computing system - Parallel computing development and programming skills - MPI development and programming skills. - Knowledge in hardware accelerators

- Knowledge in computer architecture concepts - Knowledge in multiprocessor systems - Knowledge of the main elements composing a High Performance Computing system - Parallel computing development and programming skills - MPI, OpenMP and CUDA development and programming skills. - Basic knowledge in hardware accelerators.

Prerequisiti
Pre-requirements

- Basic knowledge in computer sciences - Basic knowledge in Python programming and high level programming languages

- Basic knowledge in computer sciences - Basic knowledge in C programming and high level programming languages

Programma
Course topics

- Introduction to microprocessor architecture - Introduction to multiprocessor systems architecture - Foundation concepts and perspectives about High Performance Computing - Techniques for using and programming HPC - Parallel computation - Message Passing Interfaces (MPI) - Hardware accelerators, graphic processing units (GPU) - Laboratory sessions and examples are provided for the different topics

- Introduction to microprocessor architecture - Introduction to multiprocessor systems architecture - Foundation concepts and perspectives on High Performance Computing - Techniques for using and programming HPC - Parallel computation - Shared-memory and distributed memory programming paradigms. OpenMP and MPI. - Hardware accelerators, graphic processing units (GPU) - Laboratory sessions and examples are provided for the different topics

Sustainable development goals

Fornire un�educazione di qualit�, equa ed inclusiva, e opportunit� di apprendimento per tutti

Raggiungere l�uguaglianza di genere ed emancipare tutte le donne e le ragazze

Incentivare una crescita economica duratura, inclusiva e sostenibile, un�occupazione piena e produttiva ed un lavoro dignitoso per tutti

Note
Additional information

Additional material is provided by the lecturers in the form of course slides, practical examples and laboratory exercises.

Organizzazione dell'insegnamento
Course structure

- Class lectures: 50% of the course duration; - Extensive Class exercise time: 30% of the course duration; - Assisted laboratories: 20% of the course duration. Students are highly invited to interact with Lecturers, at lecture, exercise, and laboratory slots.

Bibliografia
Reading materials

- J.L. Hennessy, D.A. Patterson, Computer Architecture: a Quantitative Approach, Morgan Kaufmann Publishers, Inc., VI Edition, 2017 - Thomas Sterling, Maciej Brodowicz, Matthew Anderson, High Performance Computing: Modern Systems and Practices, Morgan Kaufmann Publishers, Inc., 1st Edition - December 5, 2017 Optional additional material provided by the professors.

- J.L. Hennessy, D.A. Patterson, Computer Architecture: a Quantitative Approach, Morgan Kaufmann Publishers, Inc., VI Edition, 2017 - Thomas Sterling, Maciej Brodowicz, Matthew Anderson, High Performance Computing: Modern Systems and Practices, Morgan Kaufmann Publishers, Inc., 1st Edition - December 5, 2017 Optional additional material is provided by the professors, in the form of slides, and examples.

Materiale di supporto allo studio
Study materials

Dispense; Libro di testo;

Lecture notes; Text book;

Criteri, regole e procedure per l'esame
Assessment and grading criteria

Modalit� di esame: Prova scritta (in aula); Elaborato progettuale in gruppo;

Exam: Written test; Group project;

... The examination is composed of two parts, a written part and an assignment. Written examination: The written exam is composed of questions and exercises on the course content. It lasts for 1h. The maximum score for this part is 30/30. A sufficient mark is >= 18. Assignment Students will be asked to deliver a group assignment (2 persons per group) to be developed at the end of the semester. The maximum score for this part is 30/30. A sufficient mark is >= 18. The final grade is the arithmetic mean of the two parts, provided that both of them are sufficient (>=18) An optional oral examination can be asked to the teacher, in order to improve the mark and reach the 30 cum laude.

Gli studenti e le studentesse con disabilit� o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unit� Special Needs, al fine di permettere al/la docente la declinazione pi� idonea in riferimento alla specifica tipologia di esame.

Exam: Written test; Group project;

The examination is composed of two parts, a written part and an assignment. Written examination: The written exam is composed of questions and exercises on the course content. It lasts for 1h. The maximum score for this part is 30/30. A sufficient mark is >= 18. During the examination, it is not allowed to check any supporting material. Assignment Students will be asked to deliver a group assignment (2 persons per group) to be developed at the end of the semester. The maximum score for this part is 30/30. A sufficient mark is >= 18. The assignments deadlines are organized together with the students, considering the examination dates scheduled in every semester. The final grade is the arithmetic mean of the two parts, provided that both of them are sufficient (>=18) An optional oral examination can be asked to the teacher, in order to improve the mark and reach the 30 cum laude.

In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.