1. General information
Course:
HIGH PERFORMANCE COMPUTING
Code:
311049
Type:
CORE COURSE
ECTS credits:
6
Degree:
2361 - MÁSTER UNIVERSITARIO EN INGENIERÍA INFORMÁTICA (AB) (2020)
Academic year:
2022-23
Center:
604 - SCHOOL OF COMPUTER SCIENCE AND ENGINEERING (AB)
Group(s):
10
11
Year:
1
Duration:
C2
Main language:
Spanish
Second language:
English
Use of additional languages:
English Friendly:
Y
Web site:
Bilingual:
N
Lecturer:
ENRIQUE ARIAS ANTUNEZ
- Group(s):
10
11
Building/Office
Department
Phone number
Email
Office hours
Agrupación Politécnica/ Desp. 0.A.8
SISTEMAS INFORMÁTICOS
2497
enrique.arias@uclm.es
https://www.esiiab.uclm.es/pers.php?codpers=earias&idmenup=pers&curso=2022-23
2. Pre-Requisites
Not established
3. Justification in the curriculum, relation to other subjects and to the profession
The field of High Performance Computing (HPC) and its applications has become one of the most dynamic in the world of Computer Science, making it necessary to have a thorough knowledge of this area and its characteristics. Starting from a basic knowledge of the computational infrastructure that supports the HPC, the techniques and methods for the analysis of supercomputers and their comparison, as well as the design and programming of parallel applications, will be studied in depth. The field of supercomputing is involved in many fields of engineering (e.g. simulations of complex physical and chemical processes) and business (e.g. Big Data), making its knowledge indispensable for today's ICT professionals.
4. Degree competences achieved in this course
| Course competences | |
|---|---|
| Code | Description |
| CE09 | Ability to design and assess operating systems and servers, plus applications and systems based on distributed computing. |
| CE10 | Ability to understand a apply advanced knowledge on high performance computing and numerical or computational methods to engineering problems. |
| INS01 | Analysis, synthesis and assessment skills. |
| INS04 | Problem solving skills by the application of engineering techniques. |
| INS05 | Argumentative skills to logically justify and explain decisions and opinions. |
| PER01 | Team work abilities. |
| SIS03 | Autonomous learning. |
5. Objectives or Learning Outcomes
| Course learning outcomes | |
|---|---|
| Description | |
| Manage tasks of all elements involved in the running of a high-performance distributed data processing system | |
| Design and engineer high-performance and high-availability data processing equipment, including hardware, software and human resources | |
| Evaluate and exploit the system, including socio-economic aspects | |
| Additional outcomes | |
| Description | |
| To train students to make professional and business decisions that will enable them to improve the performance and competitiveness of their organisation's ICT infrastructure. | |
| To equip the student with the ability to make professional and business decisions to improve the performance and competitiveness of their organisation's ICT infrastructure. | |
6. Units / Contents
-
Unit 1: Introduction to High Performance Computing
-
Unit 2: Performance analysis and benchmarking
-
Unit 3: High Performance Programming Models
-
Unit 4: Models and platforms
-
Unit 5: Application Deployment
ADDITIONAL COMMENTS, REMARKS
The practical sessions will consist of adjusting a theoretical model of system runtimes, determining the performance of our systems and developing distributed applications using the MPI library and OpenMP.
7. Activities, Units/Modules and Methodology
| Training Activity | Methodology | Related Competences (only degrees before RD 822/2021) | ECTS | Hours | As | Com | Description | |
| Class Attendance (theory) [ON-SITE] | Combination of methods | CE09 CE10 | 1.04 | 26 | N | N | Theory masterclasses | |
| Laboratory practice or sessions [ON-SITE] | Project/Problem Based Learning (PBL) | CE09 CE10 INS04 | 1.04 | 26 | Y | Y | All students, in groups of maximum 2, have to develop parallel implementations of a problem. Each problem is different per group. Then, the student will learn parallel programming and related libraries by doing. | |
| Workshops or seminars [ON-SITE] | Workshops and Seminars | CE09 CE10 INS04 | 0.32 | 8 | N | N | Two seminars will be held on advanced aspects of supercomputing. | |
| Individual tutoring sessions [ON-SITE] | Guided or supervised work | INS05 | 0.16 | 4 | N | N | Tutoring | |
| Study and Exam Preparation [OFF-SITE] | Self-study | SIS03 | 2.24 | 56 | N | N | Work to be done by the student both for study and test preparation. | |
| Practicum and practical activities report writing or preparation [OFF-SITE] | Self-study | INS01 PER01 | 1.08 | 27 | Y | Y | The different teams of students have to prepare a report with an hybrid implementation of the problem dealt during the semester. A presentation of this report have to be done. | |
| Final test [ON-SITE] | CE09 CE10 INS01 | 0.04 | 1 | Y | Y | This final exam will consist of an exam on concepts of the subject developed in a short answer questionnaire in the ordinary exam. This activity will be recovered by taking the exam again in the extraordinary exam. | ||
| Project or Topic Presentations [ON-SITE] | Individual presentation of projects and reports | INS01 | 0.08 | 2 | Y | Y | ||
| Total: | 6 | 150 | ||||||
| Total credits of in-class work: 2.68 | Total class time hours: 67 | |||||||
| Total credits of out of class work: 3.32 | Total hours of out of class work: 83 | |||||||
As: Assessable training activity Com: Training activity of compulsory overcoming (It will be essential to overcome both continuous and non-continuous assessment).
8. Evaluation criteria and Grading System
| Evaluation System | Continuous assessment | Non-continuous evaluation * | Description |
| Final test | 40.00% | 40.00% | (ESC) Final written exam. There will be a final short answer exam on the concepts of the subject. Also, 2 points will be achieved by the seminars. |
| Practicum and practical activities reports assessment | 20.00% | 20.00% | (INF) Preparation of a report on the laboratory practicals carried out. The final report containing all the practical exercises will be evaluated. Optionally, and as a formative action, on-site students may submit intermediate reports. In the case of blended learning students, it is compulsory. |
| Laboratory sessions | 30.00% | 30.00% | (LAB) Practical work. The laboratory practicals will be assessed by observation for on-site students and by means of the intermediate reports for blended learning students. |
| Oral presentations assessment | 10.00% | 10.00% | (PRES) Presentation in class of the final practical report. |
| Total: | 100.00% | 100.00% |
According to art. 4 of the UCLM Student Evaluation Regulations, it must be provided to students who cannot regularly attend face-to-face training activities the passing of the subject, having the right (art. 12.2) to be globally graded, in 2 annual calls per subject , an ordinary and an extraordinary one (evaluating 100% of the competences).
Evaluation criteria for the final exam:
-
Continuous assessment:The course will be passed with a mark equal to or higher than 5. A minimum of 3 points in practicum+ lab+oral must be achieved. Also, in order to validate the final test score, each student has to prepare one question per unit.
If a student has completed 50% of the evaluable activities or, if in any case, the class period has ended, he/she will be considered in continuous evaluation without the possibility of changing the evaluation modality. -
Non-continuous evaluation:The course will be passed with a mark equal to or higher than 5. A minimum of 3 points in practicum+ lab+oral must be achieved. Also, in order to validate the final test score, each student has to prepare one question per unit.
If a student has completed 50% of the evaluable activities or, if in any case, the class period has ended, he/she will be considered in continuous evaluation without the possibility of changing the evaluation modality.
Specifications for the resit/retake exam:
All grades obtained will be maintained.
The evaluation activities will be the same as in the ordinary exam.
The evaluation activities will be the same as in the ordinary exam.
Specifications for the second resit / retake exam:
All grades obtained will be maintained.
The evaluation activities will be the same as in the ordinary exam.
The evaluation activities will be the same as in the ordinary exam.
9. Assignments, course calendar and important dates
| Not related to the syllabus/contents | |
|---|---|
| Hours | hours |
| Unit 1 (de 5): Introduction to High Performance Computing | |
|---|---|
| Activities | Hours |
| Class Attendance (theory) [PRESENCIAL][Combination of methods] | 6 |
| Laboratory practice or sessions [PRESENCIAL][Project/Problem Based Learning (PBL)] | 6 |
| Individual tutoring sessions [PRESENCIAL][Guided or supervised work] | 1 |
| Study and Exam Preparation [AUTÓNOMA][Self-study] | 14 |
| Practicum and practical activities report writing or preparation [AUTÓNOMA][Self-study] | 7 |
| Unit 2 (de 5): Performance analysis and benchmarking | |
|---|---|
| Activities | Hours |
| Class Attendance (theory) [PRESENCIAL][Combination of methods] | 4 |
| Laboratory practice or sessions [PRESENCIAL][Project/Problem Based Learning (PBL)] | 2 |
| Individual tutoring sessions [PRESENCIAL][Guided or supervised work] | 1 |
| Study and Exam Preparation [AUTÓNOMA][Self-study] | 14 |
| Practicum and practical activities report writing or preparation [AUTÓNOMA][Self-study] | 7 |
| Unit 3 (de 5): High Performance Programming Models | |
|---|---|
| Activities | Hours |
| Class Attendance (theory) [PRESENCIAL][Combination of methods] | 2 |
| Unit 4 (de 5): Models and platforms | |
|---|---|
| Activities | Hours |
| Class Attendance (theory) [PRESENCIAL][Combination of methods] | 4 |
| Laboratory practice or sessions [PRESENCIAL][Project/Problem Based Learning (PBL)] | 10 |
| Individual tutoring sessions [PRESENCIAL][Guided or supervised work] | 1 |
| Study and Exam Preparation [AUTÓNOMA][Self-study] | 14 |
| Practicum and practical activities report writing or preparation [AUTÓNOMA][Self-study] | 7 |
| Unit 5 (de 5): Application Deployment | |
|---|---|
| Activities | Hours |
| Class Attendance (theory) [PRESENCIAL][Combination of methods] | 10 |
| Laboratory practice or sessions [PRESENCIAL][Project/Problem Based Learning (PBL)] | 8 |
| Workshops or seminars [PRESENCIAL][Workshops and Seminars] | 8 |
| Individual tutoring sessions [PRESENCIAL][Guided or supervised work] | 1 |
| Study and Exam Preparation [AUTÓNOMA][Self-study] | 14 |
| Practicum and practical activities report writing or preparation [AUTÓNOMA][Self-study] | 6 |
| Final test [PRESENCIAL][] | 1 |
| Project or Topic Presentations [PRESENCIAL][Individual presentation of projects and reports] | 2 |
| Global activity | |
|---|---|
| Activities | hours |
| General comments about the planning: | This course schedule is APPROXIMATE. It could vary throughout the academic course due to teaching needs, bank holidays, etc. A weekly schedule will be properly detailed and updated on the online platform (Virtual Campus). Classes will be scheduled in 2 sessions of two hours per week. Evaluation activities or catch-up classes may exceptionally be scheduled in the morning. |
10. Bibliography and Sources
| Author(s) | Title | Book/Journal | Citv | Publishing house | ISBN | Year | Description | Link | Catálogo biblioteca |
|---|---|---|---|---|---|---|---|---|---|
| Ananth Grama, George Karypis, Vipin Kumar y Anshul Gupta | Introduction to Parallel Computing | Addison Wesley | 978-0201648652 | 2003 | Accessd to digital version through UCLM library | ||||
| FRANCISCO CARMELO ALMEIDA RODRÍGUEZ, DOMINGO GIMENEZ CANOVAS, JOSÉ MIGUEL MANTAS RUÍZ, ANTONIO VIDAL MACIA | Introducción a la programación paralela | Paraninfo | 9788497326742 | 2008 | |||||
| Michael J. Quinn | Parallel Programming in C with MPI and OpenMP | McGraw Hill Higher Education | 978-0072822564 | 2003 | |||||
| Peter Pacheco | An Introduction to Parallel Programming | Morgan Kaufmann | 978-0-12-374260-5 | 2011 | http://proquest.safaribooksonline.com/book/programming/9780123742605 | ||||
| Rohit Chandra Leonardo Dagum Dave Kohr Dror Maydan Jeff McDonald Ramesh Menon | Parallel Programming in OpenMP | Morgan Kaufmann Publishers | 1-55860-671-8 | 2001 | |||||
| Roman Trobec ¿ Boštjan Slivnik Patricio Buli¿ ¿ Borut Robi¿ | Introduction to Parallel Computing From Algorithms to Programming on State-of-the-Art Platforms | Springer | 978-3-319-98832-0 | 2018 | |||||
| Thomas Sterling | High Performance Computing: Modern Systems and Practices | Morgan Kauffman | 2017 |