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.
Study Plan
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 Medical bioinformatics - Enrollment from 2025/2026The 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.
1° Year
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One course to be chosen between the followingTwo courses to be chosen among the following2° Year activated in the A.Y. 2021/2022
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One course to be chosen between the followingTwo courses to be chosen among the following| Modules | Credits | TAF | SSD |
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Three courses to be chosen among the following| Modules | Credits | TAF | SSD |
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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.
Architectures and systems for biological data processing (2021/2022)
Teaching code
4S004555
Credits
6
Language
English
Also offered in courses:
- Parallel Programming of the course Master's degree in Computer Science and Engineering
- Parallel Programming of the course Master's degree in Computer Science and Engineering
- Parallel Programming of the course Master's degree in Computer Science and Engineering
Scientific Disciplinary Sector (SSD)
ING-INF/05 - INFORMATION PROCESSING SYSTEMS
The teaching is organized as follows:
Teoria
Laboratorio
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). This knowledge will allow the student to be able to analyze performance and to 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 student will be able 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. During the definition of the optimized code structure, the student will have the ability to continue the study autonomously in the field of the parallel programming languages and of the Software development for parallel embedded platforms.
Program
Theory:
- Parallel architectures
- Parallel programming models
- Performance measurement
- Perspective on Parallel Programming
- Designing parallel programs
- GPUs and CUDA:
overview , parallel programming model, threads
memory hierarchy/model
performance considerations
optimizations
- Graph algorithms on GPUs
data representations: Adj. matriX/lists, edge lists
Parallel algorithms for graph traversal (BFS)
Parallel algorithms for graph analysis (SSSP, APSP)
Parallel algorithms for graphs: load balancing and memory accesses: issues and management
Lab:
- OpenMP
- MPI
- CUDA
Examination Methods
To pass the exam, the student has to demonstrate:
- he/she has understood the principles related to the parallel 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).
