The Master in High Performance Computing is organized by the University of A Coruña and the University of Santiago de Compostela, together with the Galicia Supercomputing Center (CESGA). Students will be specialized in a such as important today topic as High Performance Computing (HPC).
Master in High Performance Computing (In-person)
Duration:
1 academic year
RUCT code: 4316445
ECTS Number: 60
Seats number: 12
Dean or center director:
JULIA GONZALEZ ALVAREZ
Title coordinator:
Pablo Quesada Barriuso
pablo.quesada [at] usc.es
Use languages:
Spanish, Galician, English
Coordinator university:
University of A Coruña
Partaker universities:
University of Santiago de Compostela
University of A Coruña
Xunta de Galicia title implantation authorization date:
Orde do 13/06/2018 (DOG do 29/06/2018)
BOE publication date:
11/03/2019
Last accreditation date:
28/01/2019
High Performance Computing (HPC) allows scientists and engineers to solve complex science, engineering, and business problems using applications that require high bandwidth, enhanced networking, and very high computing capabilities. Professionals who have taken this specialization possess all of the knowledge and skills required by companies and institutions with R&D centers that want to incorporate emerging technologies. HPC is related to prominent topics such as multicore processors (formerly specific to large computers but nowadays present in PCs, tablets or mobile phones), cloud computing, or the so-called Big Data.
The Master in High Performance Computing has as main objective the training of professionals, technologists and researchers in the field of computer architecture and high performance computing. This affects the academic, research and technology transfer that will allow students to join research and innovation departments, high-tech centers, or begin PhD studies in the field of high performance computing.
Contributors to this master are multinationals such as IBM, HP, Atos, Fujitsu, AMD, or Gompute Amazon Web Services and the Professional Association of Computer Engineers of Galicia (CPEIG).
Duration:
1 academic year
RUCT code: 4316445
ECTS Number: 60
Seats number: 12
Dean or center director:
JULIA GONZALEZ ALVAREZ
Title coordinator:
Pablo Quesada Barriuso
pablo.quesada [at] usc.es
Use languages:
Spanish, Galician, English
Coordinator university:
University of A Coruña
Partaker universities:
University of Santiago de Compostela
University of A Coruña
Xunta de Galicia title implantation authorization date:
Orde do 13/06/2018 (DOG do 29/06/2018)
BOE publication date:
11/03/2019
Last accreditation date:
28/01/2019
High Performance Computing (HPC) allows scientists and engineers to solve complex science, engineering, and business problems using applications that require high bandwidth, enhanced networking, and very high computing capabilities. Professionals who have taken this specialization possess all of the knowledge and skills required by companies and institutions with R&D centers that want to incorporate emerging technologies. HPC is related to prominent topics such as multicore processors (formerly specific to large computers but nowadays present in PCs, tablets or mobile phones), cloud computing, or the so-called Big Data.
The Master in High Performance Computing has as main objective the training of professionals, technologists and researchers in the field of computer architecture and high performance computing. This affects the academic, research and technology transfer that will allow students to join research and innovation departments, high-tech centers, or begin PhD studies in the field of high performance computing.
Contributors to this master are multinationals such as IBM, HP, Atos, Fujitsu, AMD, or Gompute Amazon Web Services and the Professional Association of Computer Engineers of Galicia (CPEIG).
Condiciones de terminación:
Obligatorias: 27
Optativas: 12
Prácticas externas 6
Trabajo fin de máster: 15
Total: 60
No se contemplan
High Performance Architectures
- P4191101
- Compulsory Credits
- First Semester
- 6 Credits
Parallel Programming
- P4191102
- Compulsory Credits
- First Semester
- 6 Credits
Heterogenous Programming
- P4191103
- Compulsory Credits
- First Semester
- 6 Credits
High Performance Infrastructures
- P4191104
- Compulsory Credits
- First Semester
- 6 Credits
Projects Workshop
- P4191105
- Compulsory Credits
- Second Semester
- 3 Credits
HPC Tools
- P4191201
- Elective Credits
- First Semester
- 6 Credits
HPC on the Cloud
- P4191202
- Elective Credits
- First Semester
- 6 Credits
Advanced Parallel Programming
- P4191203
- Elective Credits
- Second Semester
- 6 Credits
Data analytics with HPC
- P4191204
- Elective Credits
- Second Semester
- 6 Credits
Profesional Practice
- P4191106
- Compulsory Credits
- Work Placements in Companies for Degrees and Master's Degrees
- 6 Credits
Master’s Thesis
- P4191107
- Compulsory Credits
- End of Degree Projects and End of Master's Degree Projects
- 15 Credits
The Master in High Performance Computing is organized by the University of A Coruña and the University of Santiago de Compostela, together with the Galicia Supercomputing Center (CESGA). Students will be specialized in a such as important today topic as High Performance Computing (HPC).
-
Condiciones de terminación:
Obligatorias: 27
Optativas: 12
Prácticas externas 6
Trabajo fin de máster: 15
Total: 60
Existirá un sistema de tutorías por el que todos los alumnos contarán con un docente que hará las labores de tutor personal. La lista de los tutores asignados a cada alumno matriculado se elaborará una vez cerrado el proceso de matriculación, y será aprobada por la Comisión Académica Interuniversitaria (CAI) del máster. Estará disponible para su consulta en los medios de difusión que tiene a su disposición la organización del máster. Las funciones del tutor serán las de atender las consultas del alumno, orientarle en aquellos temas que precise y apoyarle en el desarrollo de su actividad académica. Además, orientará al alumno en aquellos aspectos que puedan serle de utilidad para que, en el momento de realizar el Trabajo Fin de Máster, pueda disponer de una visión amplia y adecuada del enfoque académico del mismo. Además, el coordinador del máster será un referente tanto para el tutor personal como para el alumno. Se dará continuidad al proceso de tutorización de los estudiantes durante todos los estudios, incluyendo orientación para la posterior realización de la tesis doctoral, y eventualmente la incorporación a la vida laboral o estudios posteriores.
Access
Para acceder aos ensinos oficiais de Máster será necesario estar en posesión de:
A.1. Un título universitario oficial español.
A.2. Un título expedido por unha institución de educación superior pertencente a outro Estado integrante do Espazo Europeo de Educación Superior que faculte no mesmo para o acceso a ensinos de Máster.
A.3. Un título pertencente a un sistema educativo alleo ao Espazo Europeo de Educación, previa comprobación pola Universidade de que o citado título acredita un nivel de formación equivalente aos correspondentes títulos universitarios oficiais españois e faculta no país expedidor do título para o acceso a ensinos de posgrao.
A.4. Un título superior das Ensinanzas Artísticas Superiores do sistema educativo español.
Admission
Modality: general criteria
Access qualifications:
- Degrees in Computer Science, Computer Engineering, Telecommunications, Electronics or Industrial Engineering.
- Degrees in Physics or Mathematics.
- Other degrees in Science or Engineering and Architecture.
In addition, it will be necessary to accredit a minimum knowledge of English corresponding to level B1 of the Common European Framework of Reference for Languages. In the event that the student, exceptionally, cannot accredit it at the time of the application for admission, or even at the time of enrolment, he/she will be able to accredit it later, but always before obtaining the degree.
In the event that the places on one of the modalities are not filled, they may be accumulated to the other.
Information updated at the registration call.
Modality: general criteria
Access qualifications:
- Degrees in Computer Science, Computer Engineering, Telecommunications, Electronics or Industrial Engineering.
- Degrees in Physics or Mathematics.
- Other degrees in Science or Engineering and Architecture.
In addition, it will be necessary to accredit a minimum knowledge of English corresponding to level B1 of the Common European Framework of Reference for Languages. In the event that the student, exceptionally, cannot accredit it at the time of the application for admission, or even at the time of enrolment, he/she will be able to accredit it later, but always before obtaining the degree.
In the event that the places on one of the modalities are not filled, they may be accumulated to the other.
Information updated at the registration call.
- Poseer y comprender conocimientos que aporten una base u oportunidad de ser originales en el desarrollo y/o aplicación de ideas, a menudo en un contexto de investigación
- Que los estudiantes sepan aplicar los conocimientos adquiridos y su capacidad de resolución de problemas en entornos nuevos o poco conocidos dentro de contextos más amplios (o multidisciplinares) relacionados con su área de estudio
- Que los estudiantes sean capaces de integrar conocimientos y enfrentarse a la complejidad de formular juicios a partir de una información que, siendo incompleta o limitada, incluya reflexiones sobre las responsabilidades sociales y éticas vinculadas a la aplicación de sus conocimientos y juicios
- Que los estudiantes sepan comunicar sus conclusiones y los conocimientos y razones últimas que las sustentan a públicos especializados y no especializados de un modo claro y sin ambigüedades
- Que los estudiantes posean las habilidades de aprendizaje que les permitan continuar estudiando de un modo que habrá de ser en gran medida autodirigido o autónomo.
Students completing this master:
1. will know the architecture of the computer, of multiprocessor systems and supercomputers as well as others advanced architectures
2. will use these knowledges to increase the performance of the applications
3. will be able to generate optimised code and to apply concurrent computing techniques
4. will know the operating systems for parallel and distributed systems, its internal structure, and its associated tools
5. will be expert in evaluating the computer and codes performance
6. will know to use supercomputing techniques and the tools provide by supercomputers to resolve scientific and technical problems his/her speciality
- Definir, evaluar y seleccionar la arquitectura y el software más adecuado para la resolución de un problema
- Analizar y mejorar el rendimiento de una arquitectura o un software dado
- Conocer los conceptos y las técnicas básicas de la computación de altas prestaciones
- Profundizar en el conocimiento de herramientas de programación y diferentes lenguajes en el campo de la computación de altas prestaciones
- Analizar, diseñar e implementar algoritmos y aplicaciones paralelas eficientes
- Conocer las tecnologías y herramientas disponibles para la computación en sistemas distribuidos sobre una red
- Ser capaz de plantear, modelar y resolver problemas que necesitan de técnicas de computación de altas prestaciones
- Conocer las arquitecturas emergentes en el campo de la supercomputación
- Utilizar las herramientas básicas de las tecnologías de la información y las comunicaciones (TIC) necesarias para el ejercicio de su profesión y para el aprendizaje a lo largo de su vida
- Estimular la capacidad para trabajar en equipos interdisciplinares o transdisciplinares, para ofrecer propuestas que contribuyan a un desarrollo sostenible ambiental, económico, político y social
- Capacidad de gestionar tiempos y recursos: desarrollar planes, priorizar actividades, identificar las críticas, establecer plazos y cumplirlos
- Valorar la importancia que tiene la investigación, la innovación y el desarrollo tecnológico en el avance socioeconómico y cultural de la sociedad
- Entender la importancia de la cultura emprendedora y conocer los medios al alcance de las personas emprendedoras
Mobility
Se potenciará la movilidad tanto de profesores como de estudiantes, a través de programas de intercambio o convenios con otras universidades del ámbito nacional o internacional. Se procurará su financiación a través de concurrencia a convocatorias con estos fines existentes en la Comunidad Europea, el Ministerio de Educación, el Ministerio de Asuntos Exteriores, la Comunidad Autónoma y diversas Fundaciones.
La Comisión Académica Interuniversitaria (CAI) tendrá como función tutorizar y asistir en sus decisiones académicas a los estudiantes propios y de acogida y planificará, dotará mecanismos de seguimiento, evaluación, asignación de créditos y reconocimiento curricular de la movilidad de estudiantes tanto entre las universidades involucradas en el título como a otras universidades o centros. La selección de candidatos se llevará a cabo, para cada convocatoria o programa, por la CAI, de acuerdo con criterios de baremación, previamente establecidos, que tendrán en cuenta el expediente académico, una memoria y, en su caso, las competencias en idiomas que exige la universidad de destino.
La movilidad de los/as estudiantes está regulada a través del “Reglamento de intercambios interuniversitarios”. A través de la Oficina de Relaciones Exteriores se gestionan programas de intercambio tanto nacionales (SICUE), como europeos (ERASMUS) y extracomunitarios (intercambios con países de América Latina o países de habla inglesa):
Internships
Las prácticas vinculadas al entorno profesional consistirán en la ejecución de un trabajo asociado a competencias desarrolladas en el transcurso de la titulación. El estudiante colaborará en el desarrollo de un proyecto aplicando e integrando los conocimientos y las habilidades vinculadas al Máster HPC. La práctica fijará unos objetivos generales, unos resultados de aprendizaje y un plan de actuación. El número de créditos vinculados a las prácticas profesionales es de 6.
Las prácticas serán dirigidas por tutores de perfil I+D+i en el sector HPC. Se asignará a cada práctica un profesor-tutor (interno a la universidad) y un tutor externo (personal de la empresa o institución en la que se realicen las prácticas) propuesto por la entidad colaboradora. Ambos tutores propondrán a los estudiantes la resolución de problemas vigentes y reales en las instituciones o empresas colaboradoras y guiarán, asesorarán y evaluarán el trabajo realizado por los estudiantes. La evaluación final será realizada por el profesor-tutor a partir de los informes del tutor externo y de la presentación del estudiante de su memoria de prácticas.
El trabajo consistirá en el estudio de un tema de investigación y/o desarrollo en el campo HPC con objetivos concretos alcanzables en un corto espacio de tiempo.
Para su desarrollo existirán dos opciones:
a) La realización vinculada a una práctica desarrollada en el período de prácticas profesionales en instituciones o empresas
b) La realización independiente de dichas prácticas, que típicamente permitirá al alumno introducirse de modo práctico en un trabajo de investigación en alguna de las líneas en las que trabajan los grupos a los que pertenece el equipo docente.
En cualquier caso, al finalizar el trabajo el alumno ha de presentar una memoria final y defender el trabajo ante una comisión especializada. El Trabajo Fin de Máster solo se podrá defender una vez superados los restantes créditos de la titulación.
The teaching staff for the Master' in HPC consists of lecturers from the ETSE of the USC and from the Faculty of Computer Science of the UDC.
|
Indicator |
2018-2019 |
2019-2020 |
2020-2021 |
2021-2022 |
2022-2023 |
|
|---|---|---|---|---|---|---|
|
Offer |
||||||
|
IN01 Offered places Number of places offered for each academic year. Scale info: Whole number |
12,0 |
12,0 |
12,0 |
12,0 |
12,0 |
|
|
Enrolment |
||||||
|
IN02 Enrollment Number of students enrolled in an academic year without counting students from incoming mobility programs. Scale info: Whole number |
12,0 |
14,0 |
7,0 |
22,0 |
7,0 |
|
|
IN03 Access enrollment Number of students enrolling in a study plan for the first time. This includes students who transfer their transcripts, access by partial validation of foreign studies or who adapt from plans in extinction. Scale info: Whole number |
12,0 |
12,0 |
6,0 |
16,0 |
5,0 |
|
|
IN04 New enrollment by pre-registration Number of students who enroll in the first year of a study plan for the first time, that is, not counting students who access through partial validation of foreign studies, transfers or adaptations from plans in extinction. Scale info: Whole number |
12,0 |
12,0 |
6,0 |
9,0 |
5,0 |
|
|
IN05 Variation in new enrollment by pre-registration Relative variation rate of new admission enrollment by pre-registration. Scale info: Percentage with two decimal places. |
- |
0,0 |
-50,0 |
50,0 |
- |
|
|
Admittance profile |
||||||
|
IN06 Average access grade by pre-registration Average entrance grade for pre-registration of students starting studies. Determines the entry profile. Scale info: Rational number with two decimal places. The range goes from 0 to the maximum value that can be obtained in each academic year for pre-registration (some historical values have been 10.00 points, 12.00 points or 14.00 points). |
7,832 |
7,2125 |
7,727 |
7,8685 |
9,1 |
|
|
IN08 Percentage of foreign students over total enrolled Percentage of foreign students over enrolled students, excluding students enrolled in incoming mobility programs. Scale info: Percentage with two decimal places |
58,33 |
50,0 |
42,86 |
36,36 |
14,29 |
|
|
IN09 Percentage of national students from outside Galicia over total enrolled Percentage of national students from outside Galicia on enrolled students, without counting students enrolled in incoming mobility programs. Scale info: Percentage with two decimal places |
0,0 |
7,14 |
28,57 |
18,18 |
14,29 |
|
|
IN13 Percentage of enrolled students who are USC graduates Number of students enrolled in the master's program who graduated from USC. Scale info: Percentage with two decimal places |
- |
- |
0,0 |
22,73 |
28,57 |
|
|
Adaptation to demand |
||||||
|
IN12 Occupancy rate Number of new students entering through pre-registration divided by the places offered. Scale info: Percentage with two decimal places |
100,0 |
100,0 |
50,0 |
75,0 |
41,67 |
|
Indicator |
2018-2019 |
2019-2020 |
2020-2021 |
2021-2022 |
2022-2023 |
|
|---|---|---|---|---|---|---|
|
External mobility |
||||||
|
IN18 Percentage of students received by USC from mobility programs over total enrolled Number of students received at USC in that degree from other universities (mobility programs) divided by the number of students enrolled in the degree. Scale info: Percentage with two decimal places |
0,0 |
0,0 |
0,0 |
0,0 |
0,0 |
|
Indicator |
2018-2019 |
2019-2020 |
2020-2021 |
2021-2022 |
2022-2023 |
|---|---|---|---|---|---|
|
IN22 Percentage of graduates in an academic year who completed internships in companies or institutions during their studies Percentage relationship between graduates of a degree in an academic year who have carried out internships in companies and institutions throughout their studies, out of the total number of students graduating in that degree and in that same academic year. Scale info: Percentage with two decimal places |
80,0 |
83,33 |
100,0 |
50,0 |
100,0 |
|
Indicator |
2018-2019 |
2019-2020 |
2020-2021 |
2021-2022 |
2022-2023 |
|
|---|---|---|---|---|---|---|
|
Drop-out |
||||||
|
IN41 Dropout rate under RD 1393/2007 Percentage relationship between students in a new admission cohort who should have obtained their degree in the previous academic year and who did not enroll in either that academic year or the previous one. Scale info: Percentage with two decimal places |
- |
41,67 |
50,0 |
16,67 |
43,75 |
|
|
Assessment |
||||||
|
IN36 Evaluation rate Percentage relationship between the total number of ordinary credits for which the students applied and the total number of ordinary credits enrolled. Scale info: Percentage with two decimal places |
87,38 |
83,53 |
63,71 |
81,46 |
61,47 |
|
|
Average duration of studies |
||||||
|
IN38 Average duration of studies Average duration (in years) in which students take to complete the credits corresponding to the curriculum. Scale info: Rational number with two decimal places |
1,0 |
1,0 |
1,0 |
1,5 |
1,3333 |
|
|
Efficiency of graduates |
||||||
|
IN53 Efficiency rate (graduates' performance) Percentage ratio between the total number of credits that a student passed during the degree in which he graduated and the total number of credits in which he enrolled. Scale info: Percentage with two decimal places |
100,0 |
100,0 |
100,0 |
83,52 |
92,31 |
|
|
Students per group |
||||||
|
IN55 Average number of students enrolled in mandatory and basic training courses per theoretical group (lectures) Relationship between the number of students enrolled in compulsory basic education subjects and the number of theory groups in those subjects. Scale info: Rational number with two decimal places |
6,1429 |
6,0 |
3,0 |
7,0 |
2,5 |
|
|
IN56 Average number of students enrolled in elective courses per theoretical group (lectures) Relationship between the number of students enrolled in optional subjects and the number of theory groups in those subjects. Scale info: Rational number with two decimal places |
1,75 |
2,0 |
1,0 |
3,0 |
2,0 |
|
|
Success |
||||||
|
IN35 Success rate Percentage ratio between the total number of ordinary credits that students have passed and the total number of ordinary credits for which they have applied. Scale info: Percentage with two decimal places |
91,44 |
87,79 |
89,87 |
87,8 |
94,03 |
|
|
IN50 Success rate of graduates Percentage relationship between the total number of credits that a student passed throughout the degree from which he/she graduated and the total number of credits that he/she applied for. Scale info: Percentage with two decimal places |
100,0 |
100,0 |
100,0 |
97,38 |
100,0 |
|
|
Graduation |
||||||
|
IN37 Graduation rate Percentage ratio between students who completed their studies within the time provided for in the study plan or in an additional academic year and their entry cohort. It shows information on the degree of effectiveness of the students and the institution in relation to their academic activity. Scale info: Percentage with two decimal places |
- |
41,67 |
50,0 |
83,33 |
50,0 |
|
|
Performance |
||||||
|
IN34 Performance rate Percentage relationship between the total number of ordinary credits that students passed and the total number of ordinary credits in which they enrolled. Scale info: Percentage with two decimal places |
79,91 |
73,33 |
57,26 |
71,52 |
57,8 |
|
|
Satisfaction |
||||||
|
IN19 Students' satisfaction with external internships Average rating of the student satisfaction survey with external internships. Scale info: Minimum 0.00, maximum 5.00 |
3,9444 |
- |
- |
- |
- |
|
|
IN20 Professional tutors' satisfaction with external internships Average rating of the professional tutors' satisfaction survey with external internships. Scale info: Minimum 0.00, maximum 5.00 |
4,8333 |
- |
4,3333 |
- |
5,0 |
|
|
IN42 General satisfaction of graduates with the degree program Average rating of questions regarding satisfaction with the degree in the graduate survey. Scale info: Minimum 0.00, maximum 5.00 |
- |
- |
3,26 |
3,55 |
- |
|
|
IN46 Students' satisfaction with the teaching received Average rating of the student satisfaction survey with the teaching received. Scale info: Minimum 0.00, maximum 5.00 |
5,0 |
- |
- |
- |
- |
|
|
IN47 Teachers' satisfaction with the teaching provided Average rating of the teacher satisfaction survey with the teaching provided. Scale info: Minimum 0.00, maximum 5.00 |
4,0128 |
- |
- |
- |
4,1631 |
|
|
IN48 Response rate to the satisfaction survey Percentage of response to the satisfaction survey by students. Scale info: Percentage with two decimal places |
8,3333 |
- |
- |
- |
- |
|
Indicator |
2019-2020 |
2020-2021 |
2021-2022 |
2022-2023 |
|---|---|---|---|---|
|
IN24 Percentage of Teaching and Research Staff (PDI) with six-year research periods Percentage relationship between the PDI with six years and the total PDI with teaching in the degree and which can have six years Scale info: Percentage with two decimal places |
100,0 |
100,0 |
100,0 |
100,0 |
|
IN25 Percentage of PDI with a PhD over total PDI Percentage ratio between the doctoral PDI and the total PDI with teaching in the title. Scale info: Percentage with two decimal places |
100,0 |
100,0 |
100,0 |
100,0 |
|
IN26 Percentage of civil servant PDI over total PDI Percentage relationship between the official PDI and the total PDI with teaching in the degree. Scale info: Percentage with two decimal places |
75,0 |
75,0 |
77,78 |
87,5 |
Condiciones de terminación:
Obligatorias: 27
Optativas: 12
Prácticas externas 6
Trabajo fin de máster: 15
Total: 60
No se contemplan
High Performance Architectures
- P4191101
- Compulsory Credits
- First Semester
- 6 Credits
Parallel Programming
- P4191102
- Compulsory Credits
- First Semester
- 6 Credits
Heterogenous Programming
- P4191103
- Compulsory Credits
- First Semester
- 6 Credits
High Performance Infrastructures
- P4191104
- Compulsory Credits
- First Semester
- 6 Credits
Projects Workshop
- P4191105
- Compulsory Credits
- Second Semester
- 3 Credits
HPC Tools
- P4191201
- Elective Credits
- First Semester
- 6 Credits
HPC on the Cloud
- P4191202
- Elective Credits
- First Semester
- 6 Credits
Advanced Parallel Programming
- P4191203
- Elective Credits
- Second Semester
- 6 Credits
Data analytics with HPC
- P4191204
- Elective Credits
- Second Semester
- 6 Credits
Profesional Practice
- P4191106
- Compulsory Credits
- Work Placements in Companies for Degrees and Master's Degrees
- 6 Credits
Master’s Thesis
- P4191107
- Compulsory Credits
- End of Degree Projects and End of Master's Degree Projects
- 15 Credits
The Master in High Performance Computing is organized by the University of A Coruña and the University of Santiago de Compostela, together with the Galicia Supercomputing Center (CESGA). Students will be specialized in a such as important today topic as High Performance Computing (HPC).
-
Condiciones de terminación:
Obligatorias: 27
Optativas: 12
Prácticas externas 6
Trabajo fin de máster: 15
Total: 60
Existirá un sistema de tutorías por el que todos los alumnos contarán con un docente que hará las labores de tutor personal. La lista de los tutores asignados a cada alumno matriculado se elaborará una vez cerrado el proceso de matriculación, y será aprobada por la Comisión Académica Interuniversitaria (CAI) del máster. Estará disponible para su consulta en los medios de difusión que tiene a su disposición la organización del máster. Las funciones del tutor serán las de atender las consultas del alumno, orientarle en aquellos temas que precise y apoyarle en el desarrollo de su actividad académica. Además, orientará al alumno en aquellos aspectos que puedan serle de utilidad para que, en el momento de realizar el Trabajo Fin de Máster, pueda disponer de una visión amplia y adecuada del enfoque académico del mismo. Además, el coordinador del máster será un referente tanto para el tutor personal como para el alumno. Se dará continuidad al proceso de tutorización de los estudiantes durante todos los estudios, incluyendo orientación para la posterior realización de la tesis doctoral, y eventualmente la incorporación a la vida laboral o estudios posteriores.
Access
Para acceder aos ensinos oficiais de Máster será necesario estar en posesión de:
A.1. Un título universitario oficial español.
A.2. Un título expedido por unha institución de educación superior pertencente a outro Estado integrante do Espazo Europeo de Educación Superior que faculte no mesmo para o acceso a ensinos de Máster.
A.3. Un título pertencente a un sistema educativo alleo ao Espazo Europeo de Educación, previa comprobación pola Universidade de que o citado título acredita un nivel de formación equivalente aos correspondentes títulos universitarios oficiais españois e faculta no país expedidor do título para o acceso a ensinos de posgrao.
A.4. Un título superior das Ensinanzas Artísticas Superiores do sistema educativo español.
Admission
Modality: general criteria
Access qualifications:
- Degrees in Computer Science, Computer Engineering, Telecommunications, Electronics or Industrial Engineering.
- Degrees in Physics or Mathematics.
- Other degrees in Science or Engineering and Architecture.
In addition, it will be necessary to accredit a minimum knowledge of English corresponding to level B1 of the Common European Framework of Reference for Languages. In the event that the student, exceptionally, cannot accredit it at the time of the application for admission, or even at the time of enrolment, he/she will be able to accredit it later, but always before obtaining the degree.
In the event that the places on one of the modalities are not filled, they may be accumulated to the other.
Information updated at the registration call.
Modality: general criteria
Access qualifications:
- Degrees in Computer Science, Computer Engineering, Telecommunications, Electronics or Industrial Engineering.
- Degrees in Physics or Mathematics.
- Other degrees in Science or Engineering and Architecture.
In addition, it will be necessary to accredit a minimum knowledge of English corresponding to level B1 of the Common European Framework of Reference for Languages. In the event that the student, exceptionally, cannot accredit it at the time of the application for admission, or even at the time of enrolment, he/she will be able to accredit it later, but always before obtaining the degree.
In the event that the places on one of the modalities are not filled, they may be accumulated to the other.
Information updated at the registration call.
- Poseer y comprender conocimientos que aporten una base u oportunidad de ser originales en el desarrollo y/o aplicación de ideas, a menudo en un contexto de investigación
- Que los estudiantes sepan aplicar los conocimientos adquiridos y su capacidad de resolución de problemas en entornos nuevos o poco conocidos dentro de contextos más amplios (o multidisciplinares) relacionados con su área de estudio
- Que los estudiantes sean capaces de integrar conocimientos y enfrentarse a la complejidad de formular juicios a partir de una información que, siendo incompleta o limitada, incluya reflexiones sobre las responsabilidades sociales y éticas vinculadas a la aplicación de sus conocimientos y juicios
- Que los estudiantes sepan comunicar sus conclusiones y los conocimientos y razones últimas que las sustentan a públicos especializados y no especializados de un modo claro y sin ambigüedades
- Que los estudiantes posean las habilidades de aprendizaje que les permitan continuar estudiando de un modo que habrá de ser en gran medida autodirigido o autónomo.
Students completing this master:
1. will know the architecture of the computer, of multiprocessor systems and supercomputers as well as others advanced architectures
2. will use these knowledges to increase the performance of the applications
3. will be able to generate optimised code and to apply concurrent computing techniques
4. will know the operating systems for parallel and distributed systems, its internal structure, and its associated tools
5. will be expert in evaluating the computer and codes performance
6. will know to use supercomputing techniques and the tools provide by supercomputers to resolve scientific and technical problems his/her speciality
- Definir, evaluar y seleccionar la arquitectura y el software más adecuado para la resolución de un problema
- Analizar y mejorar el rendimiento de una arquitectura o un software dado
- Conocer los conceptos y las técnicas básicas de la computación de altas prestaciones
- Profundizar en el conocimiento de herramientas de programación y diferentes lenguajes en el campo de la computación de altas prestaciones
- Analizar, diseñar e implementar algoritmos y aplicaciones paralelas eficientes
- Conocer las tecnologías y herramientas disponibles para la computación en sistemas distribuidos sobre una red
- Ser capaz de plantear, modelar y resolver problemas que necesitan de técnicas de computación de altas prestaciones
- Conocer las arquitecturas emergentes en el campo de la supercomputación
- Utilizar las herramientas básicas de las tecnologías de la información y las comunicaciones (TIC) necesarias para el ejercicio de su profesión y para el aprendizaje a lo largo de su vida
- Estimular la capacidad para trabajar en equipos interdisciplinares o transdisciplinares, para ofrecer propuestas que contribuyan a un desarrollo sostenible ambiental, económico, político y social
- Capacidad de gestionar tiempos y recursos: desarrollar planes, priorizar actividades, identificar las críticas, establecer plazos y cumplirlos
- Valorar la importancia que tiene la investigación, la innovación y el desarrollo tecnológico en el avance socioeconómico y cultural de la sociedad
- Entender la importancia de la cultura emprendedora y conocer los medios al alcance de las personas emprendedoras
Mobility
Se potenciará la movilidad tanto de profesores como de estudiantes, a través de programas de intercambio o convenios con otras universidades del ámbito nacional o internacional. Se procurará su financiación a través de concurrencia a convocatorias con estos fines existentes en la Comunidad Europea, el Ministerio de Educación, el Ministerio de Asuntos Exteriores, la Comunidad Autónoma y diversas Fundaciones.
La Comisión Académica Interuniversitaria (CAI) tendrá como función tutorizar y asistir en sus decisiones académicas a los estudiantes propios y de acogida y planificará, dotará mecanismos de seguimiento, evaluación, asignación de créditos y reconocimiento curricular de la movilidad de estudiantes tanto entre las universidades involucradas en el título como a otras universidades o centros. La selección de candidatos se llevará a cabo, para cada convocatoria o programa, por la CAI, de acuerdo con criterios de baremación, previamente establecidos, que tendrán en cuenta el expediente académico, una memoria y, en su caso, las competencias en idiomas que exige la universidad de destino.
La movilidad de los/as estudiantes está regulada a través del “Reglamento de intercambios interuniversitarios”. A través de la Oficina de Relaciones Exteriores se gestionan programas de intercambio tanto nacionales (SICUE), como europeos (ERASMUS) y extracomunitarios (intercambios con países de América Latina o países de habla inglesa):
Internships
Las prácticas vinculadas al entorno profesional consistirán en la ejecución de un trabajo asociado a competencias desarrolladas en el transcurso de la titulación. El estudiante colaborará en el desarrollo de un proyecto aplicando e integrando los conocimientos y las habilidades vinculadas al Máster HPC. La práctica fijará unos objetivos generales, unos resultados de aprendizaje y un plan de actuación. El número de créditos vinculados a las prácticas profesionales es de 6.
Las prácticas serán dirigidas por tutores de perfil I+D+i en el sector HPC. Se asignará a cada práctica un profesor-tutor (interno a la universidad) y un tutor externo (personal de la empresa o institución en la que se realicen las prácticas) propuesto por la entidad colaboradora. Ambos tutores propondrán a los estudiantes la resolución de problemas vigentes y reales en las instituciones o empresas colaboradoras y guiarán, asesorarán y evaluarán el trabajo realizado por los estudiantes. La evaluación final será realizada por el profesor-tutor a partir de los informes del tutor externo y de la presentación del estudiante de su memoria de prácticas.
El trabajo consistirá en el estudio de un tema de investigación y/o desarrollo en el campo HPC con objetivos concretos alcanzables en un corto espacio de tiempo.
Para su desarrollo existirán dos opciones:
a) La realización vinculada a una práctica desarrollada en el período de prácticas profesionales en instituciones o empresas
b) La realización independiente de dichas prácticas, que típicamente permitirá al alumno introducirse de modo práctico en un trabajo de investigación en alguna de las líneas en las que trabajan los grupos a los que pertenece el equipo docente.
En cualquier caso, al finalizar el trabajo el alumno ha de presentar una memoria final y defender el trabajo ante una comisión especializada. El Trabajo Fin de Máster solo se podrá defender una vez superados los restantes créditos de la titulación.
The teaching staff for the Master' in HPC consists of lecturers from the ETSE of the USC and from the Faculty of Computer Science of the UDC.
|
Indicator |
2018-2019 |
2019-2020 |
2020-2021 |
2021-2022 |
2022-2023 |
|
|---|---|---|---|---|---|---|
|
Offer |
||||||
|
IN01 Offered places Number of places offered for each academic year. Scale info: Whole number |
12,0 |
12,0 |
12,0 |
12,0 |
12,0 |
|
|
Enrolment |
||||||
|
IN02 Enrollment Number of students enrolled in an academic year without counting students from incoming mobility programs. Scale info: Whole number |
12,0 |
14,0 |
7,0 |
22,0 |
7,0 |
|
|
IN03 Access enrollment Number of students enrolling in a study plan for the first time. This includes students who transfer their transcripts, access by partial validation of foreign studies or who adapt from plans in extinction. Scale info: Whole number |
12,0 |
12,0 |
6,0 |
16,0 |
5,0 |
|
|
IN04 New enrollment by pre-registration Number of students who enroll in the first year of a study plan for the first time, that is, not counting students who access through partial validation of foreign studies, transfers or adaptations from plans in extinction. Scale info: Whole number |
12,0 |
12,0 |
6,0 |
9,0 |
5,0 |
|
|
IN05 Variation in new enrollment by pre-registration Relative variation rate of new admission enrollment by pre-registration. Scale info: Percentage with two decimal places. |
- |
0,0 |
-50,0 |
50,0 |
- |
|
|
Admittance profile |
||||||
|
IN06 Average access grade by pre-registration Average entrance grade for pre-registration of students starting studies. Determines the entry profile. Scale info: Rational number with two decimal places. The range goes from 0 to the maximum value that can be obtained in each academic year for pre-registration (some historical values have been 10.00 points, 12.00 points or 14.00 points). |
7,832 |
7,2125 |
7,727 |
7,8685 |
9,1 |
|
|
IN08 Percentage of foreign students over total enrolled Percentage of foreign students over enrolled students, excluding students enrolled in incoming mobility programs. Scale info: Percentage with two decimal places |
58,33 |
50,0 |
42,86 |
36,36 |
14,29 |
|
|
IN09 Percentage of national students from outside Galicia over total enrolled Percentage of national students from outside Galicia on enrolled students, without counting students enrolled in incoming mobility programs. Scale info: Percentage with two decimal places |
0,0 |
7,14 |
28,57 |
18,18 |
14,29 |
|
|
IN13 Percentage of enrolled students who are USC graduates Number of students enrolled in the master's program who graduated from USC. Scale info: Percentage with two decimal places |
- |
- |
0,0 |
22,73 |
28,57 |
|
|
Adaptation to demand |
||||||
|
IN12 Occupancy rate Number of new students entering through pre-registration divided by the places offered. Scale info: Percentage with two decimal places |
100,0 |
100,0 |
50,0 |
75,0 |
41,67 |
|
Indicator |
2018-2019 |
2019-2020 |
2020-2021 |
2021-2022 |
2022-2023 |
|
|---|---|---|---|---|---|---|
|
External mobility |
||||||
|
IN18 Percentage of students received by USC from mobility programs over total enrolled Number of students received at USC in that degree from other universities (mobility programs) divided by the number of students enrolled in the degree. Scale info: Percentage with two decimal places |
0,0 |
0,0 |
0,0 |
0,0 |
0,0 |
|
Indicator |
2018-2019 |
2019-2020 |
2020-2021 |
2021-2022 |
2022-2023 |
|---|---|---|---|---|---|
|
IN22 Percentage of graduates in an academic year who completed internships in companies or institutions during their studies Percentage relationship between graduates of a degree in an academic year who have carried out internships in companies and institutions throughout their studies, out of the total number of students graduating in that degree and in that same academic year. Scale info: Percentage with two decimal places |
80,0 |
83,33 |
100,0 |
50,0 |
100,0 |
|
Indicator |
2018-2019 |
2019-2020 |
2020-2021 |
2021-2022 |
2022-2023 |
|
|---|---|---|---|---|---|---|
|
Drop-out |
||||||
|
IN41 Dropout rate under RD 1393/2007 Percentage relationship between students in a new admission cohort who should have obtained their degree in the previous academic year and who did not enroll in either that academic year or the previous one. Scale info: Percentage with two decimal places |
- |
41,67 |
50,0 |
16,67 |
43,75 |
|
|
Assessment |
||||||
|
IN36 Evaluation rate Percentage relationship between the total number of ordinary credits for which the students applied and the total number of ordinary credits enrolled. Scale info: Percentage with two decimal places |
87,38 |
83,53 |
63,71 |
81,46 |
61,47 |
|
|
Average duration of studies |
||||||
|
IN38 Average duration of studies Average duration (in years) in which students take to complete the credits corresponding to the curriculum. Scale info: Rational number with two decimal places |
1,0 |
1,0 |
1,0 |
1,5 |
1,3333 |
|
|
Efficiency of graduates |
||||||
|
IN53 Efficiency rate (graduates' performance) Percentage ratio between the total number of credits that a student passed during the degree in which he graduated and the total number of credits in which he enrolled. Scale info: Percentage with two decimal places |
100,0 |
100,0 |
100,0 |
83,52 |
92,31 |
|
|
Students per group |
||||||
|
IN55 Average number of students enrolled in mandatory and basic training courses per theoretical group (lectures) Relationship between the number of students enrolled in compulsory basic education subjects and the number of theory groups in those subjects. Scale info: Rational number with two decimal places |
6,1429 |
6,0 |
3,0 |
7,0 |
2,5 |
|
|
IN56 Average number of students enrolled in elective courses per theoretical group (lectures) Relationship between the number of students enrolled in optional subjects and the number of theory groups in those subjects. Scale info: Rational number with two decimal places |
1,75 |
2,0 |
1,0 |
3,0 |
2,0 |
|
|
Success |
||||||
|
IN35 Success rate Percentage ratio between the total number of ordinary credits that students have passed and the total number of ordinary credits for which they have applied. Scale info: Percentage with two decimal places |
91,44 |
87,79 |
89,87 |
87,8 |
94,03 |
|
|
IN50 Success rate of graduates Percentage relationship between the total number of credits that a student passed throughout the degree from which he/she graduated and the total number of credits that he/she applied for. Scale info: Percentage with two decimal places |
100,0 |
100,0 |
100,0 |
97,38 |
100,0 |
|
|
Graduation |
||||||
|
IN37 Graduation rate Percentage ratio between students who completed their studies within the time provided for in the study plan or in an additional academic year and their entry cohort. It shows information on the degree of effectiveness of the students and the institution in relation to their academic activity. Scale info: Percentage with two decimal places |
- |
41,67 |
50,0 |
83,33 |
50,0 |
|
|
Performance |
||||||
|
IN34 Performance rate Percentage relationship between the total number of ordinary credits that students passed and the total number of ordinary credits in which they enrolled. Scale info: Percentage with two decimal places |
79,91 |
73,33 |
57,26 |
71,52 |
57,8 |
|
|
Satisfaction |
||||||
|
IN19 Students' satisfaction with external internships Average rating of the student satisfaction survey with external internships. Scale info: Minimum 0.00, maximum 5.00 |
3,9444 |
- |
- |
- |
- |
|
|
IN20 Professional tutors' satisfaction with external internships Average rating of the professional tutors' satisfaction survey with external internships. Scale info: Minimum 0.00, maximum 5.00 |
4,8333 |
- |
4,3333 |
- |
5,0 |
|
|
IN42 General satisfaction of graduates with the degree program Average rating of questions regarding satisfaction with the degree in the graduate survey. Scale info: Minimum 0.00, maximum 5.00 |
- |
- |
3,26 |
3,55 |
- |
|
|
IN46 Students' satisfaction with the teaching received Average rating of the student satisfaction survey with the teaching received. Scale info: Minimum 0.00, maximum 5.00 |
5,0 |
- |
- |
- |
- |
|
|
IN47 Teachers' satisfaction with the teaching provided Average rating of the teacher satisfaction survey with the teaching provided. Scale info: Minimum 0.00, maximum 5.00 |
4,0128 |
- |
- |
- |
4,1631 |
|
|
IN48 Response rate to the satisfaction survey Percentage of response to the satisfaction survey by students. Scale info: Percentage with two decimal places |
8,3333 |
- |
- |
- |
- |
|
Indicator |
2019-2020 |
2020-2021 |
2021-2022 |
2022-2023 |
|---|---|---|---|---|
|
IN24 Percentage of Teaching and Research Staff (PDI) with six-year research periods Percentage relationship between the PDI with six years and the total PDI with teaching in the degree and which can have six years Scale info: Percentage with two decimal places |
100,0 |
100,0 |
100,0 |
100,0 |
|
IN25 Percentage of PDI with a PhD over total PDI Percentage ratio between the doctoral PDI and the total PDI with teaching in the title. Scale info: Percentage with two decimal places |
100,0 |
100,0 |
100,0 |
100,0 |
|
IN26 Percentage of civil servant PDI over total PDI Percentage relationship between the official PDI and the total PDI with teaching in the degree. Scale info: Percentage with two decimal places |
75,0 |
75,0 |
77,78 |
87,5 |