Fundamentals of Computers

• Teachers
• Weekly hours
• Competences
• Objectives
• Contents
• Activities
• Teaching methodology
• Evaluation methodology
• Bibliography
• Web links
• Previous capacities

Teachers

Person in charge

• Javier Verdu Mula ( )

Others

• Xavier Martorell Bofill ( )

Weekly hours

Competences

Transversal Competences

Transversals

• CT2 [Avaluable] - Sustainability and Social Commitment. To know and understand the complexity of economic and social phenomena typical of the welfare society; Be able to relate well-being to globalization and sustainability; Achieve skills to use in a balanced and compatible way the technique, the technology, the economy and the sustainability.
• CT3 [Avaluable] - Efficient oral and written communication. Communicate in an oral and written way with other people about the results of learning, thinking and decision making; Participate in debates on topics of the specialty itself.
• CT6 [Avaluable] - Autonomous Learning. Detect deficiencies in one's own knowledge and overcome them through critical reflection and the choice of the best action to extend this knowledge.

Basic

• CB1 - That students have demonstrated to possess and understand knowledge in an area of ??study that starts from the base of general secondary education, and is usually found at a level that, although supported by advanced textbooks, also includes some aspects that imply Knowledge from the vanguard of their field of study.
• CB4 - That the students can transmit information, ideas, problems and solutions to a specialized and non-specialized public.
• CB5 - That the students have developed those learning skills necessary to undertake later studies with a high degree of autonomy

Technical Competences

Especifics

• CE03 - To identify and apply the basic algorithmic procedures of computer technologies to design solutions to problems by analyzing the suitability and complexity of the proposed algorithms.
• CE05 - To be able to analyze and evaluate the structure and architecture of computers, as well as the basic components that make them up.
• CE06 - To be able to identify the features, functionalities and structure of Operating Systems and to design and implement applications based on their services.
• CE07 - To interpret the characteristics, functionalities and structure of Distributed Systems, Computer Networks and the Internet and design and implement applications based on them.
• CE11 - To identify and apply the fundamental principles and basic techniques of parallel, concurrent, distributed and real-time programming.
• CE19 - To use current computer systems, including high-performance systems, for the processing of large volumes of data from the knowledge of its structure, operation and particularities.
• CE28 - To plan, ideate, deploy and direct projects, services and systems in the field of artificial intelligence, leading its implementation and continuous improvement and assessing its economic and social impact.

Generic Technical Competences

Generic

• CG2 - To use the fundamental knowledge and solid work methodologies acquired during the studies to adapt to the new technological scenarios of the future.
• CG3 - To define, evaluate and select hardware and software platforms for the development and execution of computer systems, services and applications in the field of artificial intelligence.
• CG4 - Reasoning, analyzing reality and designing algorithms and formulations that model it. To identify problems and construct valid algorithmic or mathematical solutions, eventually new, integrating the necessary multidisciplinary knowledge, evaluating different alternatives with a critical spirit, justifying the decisions taken, interpreting and synthesizing the results in the context of the application domain and establishing methodological generalizations based on specific applications.
• CG5 - Work in multidisciplinary teams and projects related to artificial intelligence and robotics, interacting fluently with engineers and professionals from other disciplines.
• CG8 - Perform an ethical exercise of the profession in all its facets, applying ethical criteria in the design of systems, algorithms, experiments, use of data, in accordance with the ethical systems recommended by national and international organizations, with special emphasis on security, robustness , privacy, transparency, traceability, prevention of bias (race, gender, religion, territory, etc.) and respect for human rights.
• CG9 - To face new challenges with a broad vision of the possibilities of a professional career in the field of Artificial Intelligence. Develop the activity applying quality criteria and continuous improvement, and act rigorously in professional development. Adapt to organizational or technological changes. Work in situations of lack of information and / or with time and / or resource restrictions.

Objectives

1. Knowledge about the features and limitations, especially about accuracy error, of the different data representation formats in a computer
   Related competences: CB1, CE03,
   Subcompetences:
   • Implementation of basic operations
   • From the representation of basic data to advanced formats
2. Knowledge about a processor architecture based on Von Neumann model, as well as its key components
   Related competences: CG2, CG3, CT3, CB4, CE05, CE11,
   Subcompetences:
   • Understand the cost and energy consumption of executing an instruction
   • Memory hierarchy and its properties, especially the locality
   • Parallelism with SIMD
3. Knowledge about logical memory space, from how it is used to how some contents are managed
   Related competences: CB4, CE19,
   Subcompetences:
   • Usage and management of libraries in the memory
4. Knowledge about the basic concepts of an Operating System and understand the impact on performance and energy consumption of a system
   Related competences: CG4, CG9, CB5, CE06, CE11,
   Subcompetences:
   • File system and I/O
   • Memory and process management
5. Knowledge about the procedure to create and debug a program, as well as its requirements
   Related competences: CG9, CB5, CE03,
6. Ability to discus and compare the resolution of problems and practical exercises
   Related competences: CE28, CG5, CG8, CT2, CT6, CB4, CE06, CE07,
7. Understand the relation between the course and the AI area
   Related competences: CG9, CB1,

Contents

1. Course Introduction
   A brief introduction about the course, topics, and its relation with the AI area
2. Data Representation
   This lesson is focused on the data representation with different complexity levels, their limitations and the implementation of basic operations
3. Processor Architecture
   Introduction of the processor architecture, based on the Von Neumann's model, and its components
4. Memory Hierarchy
   Present the memory hierarchy properties, especially the concepts of locality and reutilization, and the potential impact on performance and energy consumption
5. Introduction of parallelism based on SIMD
   Introduction of the concept and key aspects of SIMD parallelism
6. Implications of executing an instruction
   Description of consequences related to cost, potential bottlenecks and energy consumption, from the architecture point of view, when executing an instruction
7. Logical Memory Space
   Presentation of basic points to understand the aim, build, usage, and management of the logical memory space
8. Introduction of libraries
   Presentation of the concept and purpose behind the libraries as well as the required management from the point of view of the logical memory space
9. Create Executables
   Introduction of compilation and interpretation processes, including the debugging as well. Comparison of requirements and limitations of generated executables
10. Impact of Operating Systems on performance and energy consumption
    Define Operating Systems and their key aspects that impact on the system performance and energy consumption
11. Basic components of Operating Systems
    Present I/O and File System subsystems of the Operating System, from the point of view and detail level of program developer. Besides, aspects of memory management are also introduced

Activities

Activity Evaluation act

Teaching methodology

Evaluation methodology

Bibliography

Basic:

• Computer systems : a programmer's perspective - Bryant, Randal E; O'Hallaron, David, Pearson, 2016. ISBN: 9781292101767
  https://discovery.upc.edu/discovery/fulldisplay?docid=alma991004062589706711&context=L&vid=34CSUC_UPC:VU1&lang=ca

Web links

• Documentació de l'assignatura https://docencia.ac.upc.edu/FIB/GIA/FC/

Previous capacities