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.

This information is intended exclusively for students already enrolled in this course.
If you are a new student interested in enrolling, you can find information about the course of study on the course page:

Laurea magistrale in Ingegneria e scienze informatiche - Enrollment from 2025/2026

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 enrollment year.

CURRICULUM TIPO:

1° Year 

ModulesCreditsTAFSSD
12
B
ING-INF/05
6
B
ING-INF/05
12
B
ING-INF/05

2° Year   activated in the A.Y. 2017/2018

ModulesCreditsTAFSSD
6
B
INF/01
6
B
ING-INF/05
Other activitites
4
F
-
ModulesCreditsTAFSSD
12
B
ING-INF/05
6
B
ING-INF/05
12
B
ING-INF/05
activated in the A.Y. 2017/2018
ModulesCreditsTAFSSD
6
B
INF/01
6
B
ING-INF/05
Other activitites
4
F
-
Modules Credits TAF SSD
Between the years: 1°- 2°
2 courses to be chosen among the following
6
C
INF/01
6
C
INF/01
6
C
INF/01
Between the years: 1°- 2°

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.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S02910

Coordinator

Nicola Bombieri

Credits

6

Also offered in courses:

Language

English en

Scientific Disciplinary Sector (SSD)

ING-INF/05 - INFORMATION PROCESSING SYSTEMS

Period

II sem. dal Mar 1, 2017 al Jun 9, 2017.

Learning outcomes

The course aims at providing students with skills for programming and analysis of advanced computer architectures with emphasis on multicore and GPU architectures. For each subject, theoretical lessons are given followed by practices in laboratory. At the completion of the course the students will be able to program advanced parallel architectures targeting performance in the context of complex applications or large datasets. They will also be able to analyze and to optimize performance, work efficiency, and quality of results of the parallel computation.

Program

Theory (32h):
Intro High-performance computing (HPC)
Parallel architectures
Parallel programming models
HPC and Symmetric Multi-Processors (SMP): OpenMP
HPC and Message Passing Interface (MPI): OpenMPI
Graphic Processing Units (GPUs): overview, parallel programming model, threads, memory model.
Performance measurement
GPU performance considerations
GPU data transfers and streams.
Parallel graph algorithms for GPUs: BFS and SSSP
OpenCL and OpenACC
Modeling for qualitative simulation in Systems Biology targeting HPC

Lab (24h):
OpenMP
OpenMPI
CUDA
OpenCL
R parallel pack
Qualitative modelling lab.

Reference texts
Author Title Publishing house Year ISBN Notes
John L. Hennessy, David A. Patterson Computer Architecture - A Quantitative Approach (Edizione 5) Morgan Kaufmann 2011 012383872X
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

Examination Methods

The exam consists of a project agreed upon with the teacher after request by email and appointment for the elaboration of the specifications (the project is valid throughout the academic year). The projects have different levels of difficulty. Every difficulty corresponds to a maximum evaluation value. Students will hold an interview to comment the project

Attendees at the course will be able to expose to the class their project, the research context in which the project is located, and the state of progress of the course.

Voting for the project (project_mark) is expressed in thirty.

The final vote is calculated as min(31, (project_mark + Bias)).
Bias is expressed in the interval [-4, + 4] and reflects the maturation and scientific autonomy acquired during the development of the project, in the exposure and in the interpretation of the scientific literature and the scientific context of the project.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE