High Performance Computing

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About

The master’s degree gives the best foundations in the fields of computer architecture and/or supercomputing. Graduates will have in-depth knowledge of digital systems and microprocessor design, supercomputer systems and parallel programming.

Destinataris

The master’s degree is aimed at students who have a bachelor’s degree in the fields of Engineering (e.g., Computer Science, Electrical Engineering Telecommunications Engineering) or Applied Sciences (e.g., Mathematics, Physics, Biology) and are pursuing a better understanding of High-Performance Computing fields and, more specifically, Supercomputing, Computer Architecture and Technology.
 

Specialization coordinator

Person Department Email
Llosa Espuny, Josep AC

Specialization teachers

Person Department Email
Alvarez Martinez, Carlos AC
Canal Corretger, Ramon AC
Costa Prats, Juan José AC
Espasa Sans, Roger AC
González Colás, Antonio Maria AC
Gonzàlez Tallada, Marc AC
Guitart Fernandez, Jordi AC
Herrero Zaragoza, Josep Ramon AC
Jimenez Gonzalez, Daniel AC
Juan Hormigo, Antonio AC
Kosmidis, Leonidas AC
Labarta Mancho, Jesus Jose AC
Larriba Pey, Josep AC
Llosa Espuny, Josep AC
Torres Viñals, Jordi AC

Technical Competences of each Specialization

HIGH PERFORMANCE COMPUTING

  • CEE4.1
    Capability to analyze, evaluate and design computers and to propose new techniques for improvement in its architecture.
  • CEE4.2
    Capability to analyze, evaluate, design and optimize software considering the architecture and to propose new optimization techniques.
  • CEE4.3
    Capability to analyze, evaluate, design and manage system software in supercomputing environments.

Subjects

Specialization compulsory subjects

Specialization complementary subjects

 

Elective
Mandatory
Master's Thesis
Mandatory Common Course

 

Semester 1

Semester 2

Semester 3

Semester 4

Seminar activities

The activities to obtain the SIRI credits can be done in any semester of the master's degree. Consult the detail of the seminars.

Specialization Elective

You can choose five of this eight courses

Microarchitecture and Processors Design

Supercomputing

Elective

Data Visualization
(DV - 6 ECTS)

Machine Learning Systems in Production
(MLOps - 6 ECTS)