- -
UPV
 

Master's Degree in Cloud and High-Performance Computing Vera (València) Campus, Universitat Politècnica de València

Master's Degree in Cloud and High-Performance Computing

60 credits

Credit €
(2021/2022)
Give access to scholarships

25 openings
(2022/2023)

Pre-registration: from 15th to 30th June

Introduction

There is currently a growing demand for professionals capable of handling tools for processing large volumes of data. Efficient management of this data is required at all levels of a computing system, from the cores of a processor to the most sophisticated cloud systems. These tools are essential for, among many other applications, running complex simulations of physical processes, designing increasingly accurate meteorological models, driving advances in genomics, analysing the massive data on the basis of which today's corporations draw up market plans and strategies (Data Management) or resolving engineering problems that require a large computational capacity, either because of their size or because the response must be given in real time.

Objectives

Training of professionals:

  • with a broad knowledge of parallel algorithmics and skills and abilities in the use of software and hardware tools that enable the development of programs on parallel computing systems.
  • able to apply parallel computing techniques for solving large-scale problems and real-time problem solving.
  • able to model engineering and scientific problems using High-Performance Computing techniques.
  • Computer Science specialists with a good understanding of the analysis and application of numerical algorithms, visualisation techniques and how algorithms use current data structures and computer architectures, as well as network technologies that allow access to remote computers.
  • with extensive knowledge of the design and development of robust and elastic distributed applications that can be deployed on cloud systems..
  • with a sufficient basis for designing applications to ensure the continuity of their service, even when they are upgraded.
  • with extensive knowledge of cloud platform architectures.
  • master the main technologies and tools for the efficient processing of big data, the creation of scalable cloud architectures and the use of distributed computing infrastructures..

Aimed at

  • Engineers, computer science graduates, telecommunications engineers, industrial engineers, physics and mathematics graduates.
  • Graduates of other engineering degrees with a teaching load equivalent to 180 ECTS credits, and engineers from other countries with similar characteristics to those mentioned above.

Admission criteria

The Academic Committee of the Master's Degree will analyse the applications and decide whether the candidates meet the academic requirements for admission to the master's degree. This Committee will establish a scale, based mainly on the academic record of the applicants and the affinity of their previous studies with the content of the master's degree, which will be used to select the candidates.

Organisation

Department of Computer Systems and Computation

Participants

Department of Computer Systems and Computation (DSIC); Institute for Instrumentation for Molecular Imaging (I3M), and Computer Technology Institute (ITI).

Cofinancing

Ministry of Education


EMAS upv