Study programme competencies |
Code
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Study programme competences / results
|
A4 |
Conocer la estructura, organización, funcionamiento e interconexión de los sistemas informáticos (computador, sistemas operativos y redes de computadores). |
A5 |
Comprender y aplicar los principios y técnicas básicas de la programación paralela y distribuida para el desarrollo y ejecución eficiente de las técnicas de inteligencia artificial. |
A6 |
Capacidad para realizar el análisis, diseño, implementación de aplicaciones que requieran trabajar con grandes volúmenes de datos, aplicando arquitecturas hardware/software adecuadas. |
B2 |
Que el alumnado sepa aplicar sus conocimientos a su trabajo o vocación de una forma profesional y posea las competencias que suelen demostrarse por medio de la elaboración y defensa de argumentos y la resolución de problemas dentro de su área de estudio. |
B5 |
Que el alumnado haya desarrollado aquellas habilidades de aprendizaje necesarias para emprender estudios posteriores con un alto grado de autonomía. |
B7 |
Capacidad para resolver problemas con iniciativa, toma de decisiones, autonomía y creatividad. |
B10 |
Capacidad para concebir nuevos sistemas computacionales y/o evaluar el rendimiento de sistemas existentes, que integren modelos y técnicas de inteligencia artificial. |
C3 |
Capacidad para crear nuevos modelos y soluciones de forma autónoma y creativa, adaptándose a nuevas situaciones. Iniciativa y espíritu emprendedor. |
Learning aims |
Learning outcomes |
Study programme competences / results |
To understand the interrelationship between operating system's software and the hardware on which it runs. |
A4 A6
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B10
|
|
To know the different models of parallel systems and their programming |
A5
|
B7 B10
|
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Be able to develop codes that make optimal use of the hardware resources available on the computer. |
A4 A5 A6
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B2 B7
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Being able to develop codes that run in parallel systems of concurrent, shared and distributed memory, as well as in hardware accelerators |
A4 A6
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B2 B7
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C3
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To understand the importance of development, analysis and optimization of parallel codes in the context of Artificial Intelligence. |
|
B5 B10
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C3
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Contents |
Topic |
Sub-topic |
Chapter 1 - Introduction and previous concepts |
* The process and sequential program
* Lifecycle of a process
* Threads
* Paralell program
* Usefulness of parallelism |
Chapter 2 - Hardware parellelism, hierarchy |
* Levels of parallelism
* Internal processor parallelism (hidden)
* Processor functionalities (low-level parallelism)
* Processor accessible resources (high-level parallelism)
* Pool of machines (Cluster and Supercomputer)
* Distributed computing
* Specific devices
* State of the art of processors |
Chapter 3 - Software parallelism, design and implementation |
* Flynn taxonomy
* Frameworks and languages for parallelism
* Key concepts
* Paradigms for parallel processing
* Parallel programs analysis
* Parallel programs design |
Chapter 4 - Parallelism for Artificial Intelligence |
* Parallelism in IA application
* Massive and distributed data processing
* Data processing in GPU |
Planning |
Methodologies / tests |
Competencies / Results |
Teaching hours (in-person & virtual) |
Student’s personal work hours |
Total hours |
Guest lecture / keynote speech |
A4 A5 B5 B10 C3 |
30 |
20 |
50 |
Laboratory practice |
A5 A6 B2 B5 B7 B10 |
30 |
50 |
80 |
Objective test |
A4 B2 B5 B7 B10 C3 |
3 |
11 |
14 |
|
Personalized attention |
|
6 |
0 |
6 |
|
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. |
Methodologies |
Methodologies |
Description |
Guest lecture / keynote speech |
* Theory sessions will introduce the basic knowledge later used on practice sessions.
* Other concepts will also be explained in detail, either because they are key to understand the technologies and techniques used on the practice sessions, or because they are more advanced and are crucial to understand the paper that parallelism has on nowadays society.
________________________________________________________________________________ |
Laboratory practice |
* Each practice lessons will be briefly explained by the teacher on a lesson class, and the students are expected to start it right away.
* Practice sessions will be self-contained and will deal with several specific problems or scenarios where parallelism plays an important role and where previously explained techniques or technologies are used.
* Each practice will focus on a single scenario or problem and will be composed of previous description and explanation, a proposed code to be analyzed and used, and a series of questions to work on. The student will have to work on the practice, starting on its first practice session and then continuing on its out-of-classroom time. The questions can range from performing an extension of the code, to performing an empirical study of its performance using several parallelism configurations, describing its behavior or functioning, or other types of questions overall focused at assessing the degree to which the student comprehended the problem and the solution.
____________________________________________ |
Objective test |
* At the end of the term, and exam will be carried out to evaluate all the subject's knowledge, primarily the concepts from the theory sessions, but also to a lesser extent the ones from the practice sessions. |
Personalized attention |
Methodologies
|
Guest lecture / keynote speech |
Laboratory practice |
|
Description |
* Personalized attention will focus on supporting the students with the overall subject.
* On the one hand, personalized attention will be available for those that have some issue understanding any concept exposed on the theory sessions, so that no student has any difficulty in keeping up with the classes and with those topics that will be the subject of evaluation.
* On the other hand, personalized attention will also be available for any student that requires some help with specific issues that arise from the practice lessons, whether they are due to technical problems or more deep understanding issues of the key concepts dealt with. Although this help will be available for any practice lesson throughout the term, it is advisable to deal with any doubt or problem either during the practice lesson or shortly afterwards.
____________________________________________________________________________
Those students with an approved dispensation for non-attendance at classes can also benefit by using this personalized attention to ask for the practice briefing as it was given during the ordinary practice classes. |
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Assessment |
Methodologies
|
Competencies / Results |
Description
|
Qualification
|
Laboratory practice |
A5 A6 B2 B5 B7 B10 |
* All the practice lessons will be assessed and graded. Such assessments can be individual using a questionare, or in a group through a submission. Groups will be formed previously and once created, can not be changed throughout the course.
* The dates and timelines for practice assessments and submissions will be previously informed to the students.
________________________________________________________________________ |
50 |
Objective test |
A4 B2 B5 B7 B10 C3 |
* Written exam carried out individually at the end of the term.
* It will mainly evaluate and assess concepts from the theory lessons.
* To a lesser point, some questions will also be present to re-asses key concepts from the practice lessons. |
50 |
|
Assessment comments |
- In order to pass the subject:
- a minimum of 40% is required on the objective test, or final exam (2 points out of 5).
- a minimum of 40% is required on the practice lessons (2 points out of 5).
- Practice sessions will be NON REPEATABLE for the second chance.
- Part-time students can attend any practice class group, once it has been previously notified.
- Part-time students or students with approved dispensation for non-attendance at classes can submit their practice lessons taking into account the longest group-specific deadline available. In case a practice lesson is assessed using a quiz, a different date will be previously negotiated if needed.
- In order to comply with the current legislation in regards to gender equality, 2 measures will be taken:
- Parity groups are to be formed, as much as possible
- All the quizzes and the final objective test will be corrected using a blind method in order to assure the student's anonimity.
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Sources of information |
Basic
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------------------------ (Tema 1). ------------------------.
------------------------ (Tema 2). ------------------------ .
------------------------ (Tema 3). ------------------------ .
------------------------ (Tema 4). ------------------------ .
Julio Ortega Lopera (2005). Arquitectura de computadores . Madrid : Thomson
David A. Patterson (2014). Computer organization and design: the hardware/software interface . Waltham, MA : Morgan Kaufmann
Sarah L. Harris (2021). Digital design and computer architecture . Amsterdam : Elsevier, Morgan Kaufmann
Francisco Almeida (2008). Introducción a la programación paralela. Madrid : Paraninfo Cengage Learning
Tomasz Drabas (2017). Learning PySpark . Packt Publishing
Jan Palach (2014). Parallel programming with Python . Packt Publishing
Alberto García García (2020). Programación de GPUs usando Compute Unified Device Architecture (CUDA). Paracuellos del Jarama : Ra-M
Giancarlo Zaccone (2015). Python parallel programming cookbook . Packt Publishing
Jesús Carretero Pérez (2021). Sistemas operativos: una visión aplicada. Madrid : McGraw-Hill |
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Complementary
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Peter S. Pacheco (2021). An introduction to parallel programming . Burlington, MA : Morgan Kaufmann
John L. Hennesy (2019). Computer architecture: a quantitative approach. Cambridge, Massachusetts : Morgan Kaufmann
Bertil Schmidt (2017). Parallel programming: concepts and practice . Cambridge, MA : Morgan Kaufmann
Jorge Luis Ortega-Arjona (2010). Patterns for parallel software design. Sussex, UK: Wiley series in software design patterns
John Cheng (2014). Professional CUDA C programming. Hoboken : John Wiley & Sons
William Stallings (2005). Sistemas operativos: aspectos internos y principios de diseño . Madrid : Pearson |
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Recommendations |
Subjects that it is recommended to have taken before |
Programming I/614G03006 | Programming II/614G03007 | Introduction to Computers/614G03012 |
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Subjects that are recommended to be taken simultaneously |
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Subjects that continue the syllabus |
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Other comments |
- It is recommended to have some knowledge and ability to program with Python, as all it will be the language used for all of the practice lessons.
- It is recommended to have some degree of expertise with a Linux operating system, mainly process and filesystem management.
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