Studying at the University of Verona

Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.

A.A. 2019/2020

Academic calendar

The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.

Academic calendar

Course calendar

The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..

Definition of lesson periods
Period From To
I semestre Oct 1, 2019 Jan 31, 2020
II semestre Mar 2, 2020 Jun 12, 2020
Exam sessions
Session From To
Sessione invernale d'esame Feb 3, 2020 Feb 28, 2020
Sessione estiva d'esame Jun 15, 2020 Jul 31, 2020
Sessione autunnale d'esame Sep 1, 2020 Sep 30, 2020
Degree sessions
Session From To
Sessione Estiva. Jul 16, 2020 Jul 16, 2020
Sessione Autunnale. Oct 15, 2020 Oct 15, 2020
Sessione Invernale. Mar 18, 2021 Mar 18, 2021
Holidays
Period From To
Festa di Ognissanti Nov 1, 2019 Nov 1, 2019
Festa dell'Immacolata Dec 8, 2019 Dec 8, 2019
Vacanze di Natale Dec 23, 2019 Jan 6, 2020
Vacanze di Pasqua Apr 10, 2020 Apr 14, 2020
Festa della Liberazione Apr 25, 2020 Apr 25, 2020
Festa del lavoro May 1, 2020 May 1, 2020
Festa del Santo Patrono May 21, 2020 May 21, 2020
Festa della Repubblica Jun 2, 2020 Jun 2, 2020
Vacanze estive Aug 10, 2020 Aug 23, 2020

Exam calendar

Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.

Exam calendar

Should you have any doubts or questions, please check the Enrolment FAQs

Academic staff

A B C D F G L M P S

Accordini Simone

simone.accordini@univr.it +39 045 8027657

Baruffi Maria Caterina

mariacaterina.baruffi@univr.it

Belussi Alberto

alberto.belussi@univr.it +39 045 802 7980

Bicego Manuele

manuele.bicego@univr.it +39 045 802 7072

Bombieri Nicola

nicola.bombieri@univr.it +39 045 802 7094

Boscaini Maurizio

maurizio.boscaini@univr.it

Busato Federico

federico.busato@univr.it

Calanca Andrea

andrea.calanca@univr.it +39 045 802 7847

Cicalese Ferdinando

ferdinando.cicalese@univr.it +39 045 802 7969

Combi Carlo

carlo.combi@univr.it 045 802 7985

Constantin Gabriela

gabriela.constantin@univr.it 045-8027102

Cristani Matteo

matteo.cristani@univr.it 045 802 7983

Daducci Alessandro

alessandro.daducci@univr.it +39 045 8027025

Dall'Alba Diego

diego.dallalba@univr.it +39 045 802 7074

Delledonne Massimo

massimo.delledonne@univr.it 045 802 7962; Lab: 045 802 7058

Franco Giuditta

giuditta.franco@univr.it +39 045 802 7045

Giacobazzi Roberto

roberto.giacobazzi@univr.it +39 045 802 7995

Giugno Rosalba

rosalba.giugno@univr.it 0458027066

Laudanna Carlo

carlo.laudanna@univr.it 045-8027689

Liptak Zsuzsanna

zsuzsanna.liptak@univr.it +39 045 802 7032

Malerba Giovanni

giovanni.malerba@univr.it 045/8027685

Marcon Alessandro

alessandro.marcon@univr.it +39 045 802 7668

Maris Bogdan Mihai

bogdan.maris@univr.it +39 045 802 7074

Perduca Massimiliano

massimiliano.perduca@univr.it +39 045 802 7984

Sala Pietro

pietro.sala@univr.it 0458027850

Salvagno Gian Luca

gianluca.salvagno@univr.it 045 8124308-0456449264

Study Plan

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University. Please select your Study Plan based on your enrolment year.

ModulesCreditsTAFSSD
Final exam
24
E
-

2° Year

ModulesCreditsTAFSSD
Final exam
24
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°
English B2
4
F
-
Between the years: 1°- 2°
Between the years: 1°- 2°
Other activities
2
F
-

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S004555

Credits

6

Coordinatore

Nicola Bombieri

Scientific Disciplinary Sector (SSD)

ING-INF/05 - INFORMATION PROCESSING SYSTEMS

Language

English

The teaching is organized as follows:

Teoria

Credits

4

Period

II semestre

Academic staff

Nicola Bombieri

Laboratorio

Credits

2

Period

II semestre

Academic staff

Nicola Bombieri

Learning outcomes

This course aims at providing theoretical and practical knowledge about programming and analysis of advanced computational architectures, with emphasis on multiprocessor and GPU platforms. At the end of the course the student will have to demonstrate the ability to apply the knowledge necessary to: identify techniques for parallel programming, also in a research context, through analysis of application efficiency and by considering both functional and non-functional design constraints (correctness, performance, energy consumption); analyze performance and perform code profiling, by identifying critical zone and the corresponding optimizations by considering the architectural characteristics of the platform; demonstrate ability to compare parallel patterns and to select the best one by considering the use case; by defining the structure of the optimized code, demonstrate the ability to identify the proper architectural choices, by considering the target application and platform contexts. Finally, the student will have to demonstrate the ability to be able to continue the study autonomously in the field of the parallel programming languages and of the Software development for parallel embedded platforms.

Program

Theory module (32 h):
-) Intro to parallelism and parallel architectures.
-) Programming parallel architectures.
-) Models of parallel programming.
-) Measurement and analysis of performance, Amdhal’s low and metrics for performance analysis.
-) Pipeline: basic and advanced concepts.
-) Instruction-level parallelism (ILP).
-) Advanced techniques of branch prediction, static scheduling, and speculation.
-) Memory hierarchy: basic and advanced concepts.
-) Advanced optimization techniques of cache performance.
-) Thread-level parallelism (TLP).
-) Cache coherency in shared-memory architectures, Snoopy protocols.
-) General purpose Graphic Processing Unit (GP-GPU).
-) Intro to non-functional contraints: power consumption and energy efficiency.
-) Deep learning at-the-edge: models and inference with architectural constraints (performance, energy efficiency, memory bandwidth, etc.).
-) Quantization and pruning of neural networks for inference on embedded architectures.

Lab module (24 h):
-) Parallel compilers for multicore architectures (OpenMP).
-) Paralle compilers for cluster architectures (MPI).
-) GP-GPU programming: CUDA.
-) Intelligent Video Analisys (Deep Learning + stream analisys) on embedded architectures.

Examination Methods

To pass the exam, the student has to demonstrate:
- he/she has understood the principles related to the parallel architectures
- he/she is able to describe the concepts in a clear and exhaustive way without digressions
- he/she is able to apply the acquired knowledge to solve application scenarios described by means of exercises, questions and projects.

The exam consists of a written test, which contains questions with multiple answers, questions with open answers, and exercises related both the theoretical and lab modules. Alternatively, the student can elaborate a project assigned by the teacher.

Bibliografia

Reference texts
Activity Author Title Publishing house Year ISBN Notes
Teoria John Hennessy, David Patterson Computer Architecture - A Quantitative Approach (Edizione 6) Morgan Kaufmann 2018 9780128119051
Teoria David B. Kirk, Wen-mei W. Hwu Programming Massively Parallel Processors - A Hands-on Approach (Edizione 3) Morgan Kaufmann 2017 978-0-12-811986-0

Type D and Type F activities

1° periodo di lezioni From 9/30/19 To 12/14/19
years Modules TAF Teacher
1° 2° The fashion lab (1 ECTS) D Not yet assigned
I semestre From 10/1/19 To 1/31/20
years Modules TAF Teacher
1° 2° Python programming language D Maurizio Boscaini (Coordinatore)
II semestre From 3/2/20 To 6/12/20
years Modules TAF Teacher
1° 2° CyberPhysical Laboratory D Andrea Calanca (Coordinatore)
1° 2° C++ Programming Language D Federico Busato (Coordinatore)
1° 2° Matlab-Simulink programming D Bogdan Mihai Maris (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
1° 2° Corso Europrogettazione D Not yet assigned
1° 2° The course provides an introduction to blockchain technology. It focuses on the technology behind Bitcoin, Ethereum, Tendermint and Hotmoka. D Matteo Cristani

Career prospects


Module/Programme news

News for students

There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details.

Attendance

As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, attendance at the course of study is not mandatory.
Please refer to the Crisis Unit's latest updates for the mode of teaching.

Gestione carriere


Graduation


Further services

I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.