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.
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.
Course calendar
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
| Period | From | To |
|---|---|---|
| I semestre | Oct 1, 2020 | Jan 29, 2021 |
| II semestre | Mar 1, 2021 | Jun 11, 2021 |
| Session | From | To |
|---|---|---|
| Sessione invernale d'esame | Feb 1, 2021 | Feb 26, 2021 |
| Sessione estiva d'esame | Jun 14, 2021 | Jul 30, 2021 |
| Sessione autunnale d'esame | Sep 1, 2021 | Sep 30, 2021 |
| Session | From | To |
|---|---|---|
| Sessione Estiva | Jul 15, 2021 | Jul 15, 2021 |
| Sessione Autunnale | Oct 15, 2021 | Oct 15, 2021 |
| Sessione Invernale | Mar 15, 2022 | Mar 15, 2022 |
| Period | From | To |
|---|---|---|
| Festa dell'Immacolata | Dec 8, 2020 | Dec 8, 2020 |
| Vacanze Natalizie | Dec 24, 2020 | Jan 3, 2021 |
| Epifania | Jan 6, 2021 | Jan 6, 2021 |
| Vacanze Pasquali | Apr 2, 2021 | Apr 5, 2021 |
| Santo Patrono | May 21, 2021 | May 21, 2021 |
| Festa della Repubblica | Jun 2, 2021 | Jun 2, 2021 |
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.
Should you have any doubts or questions, please check the Enrolment FAQs
Academic staff
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.
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
1° Year
| Modules | Credits | TAF | SSD |
|---|
2° Year
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
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.
Advanced Computer Architectures (2021/2022)
Teaching code
4S009012
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
The teaching is organized as follows:
Teoria
Laboratorio
Learning outcomes
The course aims at providing theoretical and practical knowledge about programming and analysis of advanced computing architectures, with emphasis on parallel and heterogeneous embedded platforms. At the end of the course the student will have to demonstrate the ability to apply the knowledge necessary to identify techniques for embedded software programming for edge computing, also in a research context, through analysis of application efficiency and by considering both functional and non-functional design constraints (correctness, performance, power consumption, energy efficiency). This knowledge will allow the student to analyze performance and perform code profiling, by identifying critical zone and the corresponding optimizations by considering the architectural characteristics of the platform. At the end of the course, the students will demonstrate the ability to compare parallel patterns for embedded software development and to select the best one by considering the use case. By defining the structure of the optimized code, the student will 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 continue the study autonomously in the field of the parallel programming languages and techniques for the software development for parallel and heterogeneous embedded platforms.
Program
Theory (32 h):
-) Intro to advanced computer architectures.
-) Parallel programming models and programming models for programmable edge devices.
-) Performance measurements and analysis, Amdhal law, metrics.
-) Power consumption and energy efficiency: programming models
-) Data-level parallelism: GPU e CPU-iGPU architectures
-) Pipeline: basic and advanced concepts
-) Instruction-level parallelism (ILP).
-) Branch prediction, static scheduling and speculation.
-) Memory hierarchy: basic and advanced concepts
-) Advanced techniques for cache performance optimization.
-) Thread-level parallelism (TLP).
-) Cache coherency in shared-memory architectures, Snoopy protocols.
-) Edge computing and Deep Learning at the edge
Lab (24 h):
-) Programming heterogeneous architectures (CPU-iGPU)
-) Parallel compilers for multi-core architectures
-) CNN-based inference and transfer learning at the edge
Bibliography
Examination Methods
To pass the exam, the student has to demonstrate:
- he/she has understood the principles related to the advanced computer architecture programming
- 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. The student can elaborate a project assigned by the teacher for a bonus (up to +5 points).
Type D and Type F activities
Le attività formative in ambito D o F comprendono gli insegnamenti impartiti presso l'Università di Verona o periodi di stage/tirocinio professionale.
Nella scelta delle attività di tipo D, gli studenti dovranno tener presente che in sede di approvazione si terrà conto della coerenza delle loro scelte con il progetto formativo del loro piano di studio e dell'adeguatezza delle motivazioni eventualmente fornite.
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Matlab-Simulink programming | D |
Bogdan Mihai Maris
(Coordinatore)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Introduction to 3D printing | D |
Franco Fummi
(Coordinatore)
|
| 1° 2° | Python programming language | D |
Vittoria Cozza
(Coordinatore)
|
| 1° 2° | HW components design on FPGA | D |
Franco Fummi
(Coordinatore)
|
| 1° 2° | Rapid prototyping on Arduino | D |
Franco Fummi
(Coordinatore)
|
| 1° 2° | Protection of intangible assets (SW and invention)between industrial law and copyright | D |
Roberto Giacobazzi
(Coordinatore)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | The fashion lab (1 ECTS) | D |
Maria Caterina Baruffi
(Coordinatore)
|
| 1° 2° | The course provides an introduction to blockchain technology. It focuses on the technology behind Bitcoin, Ethereum, Tendermint and Hotmoka. | D |
Nicola Fausto Spoto
(Coordinatore)
|
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.
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.
Graduation
List of theses and work experience proposals
| theses proposals | Research area |
|---|---|
| Domain Adaptation | Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems - Computer graphics, computer vision, multi media, computer games |
| Domain Adaptation | Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video) |
| Domain Adaptation | Computing Methodologies - IMAGE PROCESSING AND COMPUTER VISION |
| Domain Adaptation | Computing methodologies - Machine learning |
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.
