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Educational guide | |||||||||||||||||||||||||||||||||||||||
IDENTIFYING DATA | 2024_25 | |||||||||||||||||||||||||||||||||||||||
Subject | COMPUTER ARCHITECTURE | Code | 00709020 | |||||||||||||||||||||||||||||||||||||
Study programme |
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Descriptors | Credit. | Type | Year | Period | ||||||||||||||||||||||||||||||||||||
6 | Compulsory | Second | Second |
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Language |
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Prerequisites | ||||||||||||||||||||||||||||||||||||||||
Department | ING.MECANICA,INFORMAT.AEROESP. |
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Coordinador |
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vriec@unileon.es mcong@unileon.es |
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Lecturers |
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Web | http://agora.unileon.es | |||||||||||||||||||||||||||||||||||||||
General description | Computer architecture, parallelism, multiprocessors | |||||||||||||||||||||||||||||||||||||||
Tribunales de Revisión |
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Competencias |
Code | |
A18102 | |
B5613 | |
B5614 | |
B5615 | |
B5619 | |
B5620 | |
B5623 | |
B5624 | |
B5625 | |
B5626 | |
B5631 | |
C2 | CMECES2 That students know how to apply their knowledge to their work or vocation in a professional manner and possess the skills that are usually demonstrated through the development and defense of arguments and the resolution of problems within their area of study. |
C4 | CMECES4 That students can transmit information, ideas, problems and solutions to both a specialised and non-specialised audience |
Learning aims |
Competences | |||
To know and understand computers architecture fundamentals and also their main components | A18102 |
B5624 B5625 |
C2 C4 |
To know and apply methodologies and tools to estimate and compare computers performance | A18102 |
B5614 B5619 B5623 B5625 B5626 B5631 |
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A18102 |
B5615 |
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A18102 |
B5620 |
C4 |
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B5613 B5614 B5623 |
Contents |
Topic | Sub-topic |
Block I. FUNDAMENTALS OF QUANTITATIVE DESIGN AND ANALYSIS | Chapter 1. INTRODUCTION TO COMPUTERS ARCHITECTURES Basics about computers architectures, classes of computers, computers architectures evolution. Chapter 2. TRENDS IN TECHNOLOGY, POWER, ENERGY AND COST Main issues that have been evolving with computer architectures and constrain their performance. Chapter 3. DEPENDABILITY AND PERFORMANCE Different factors that affect to dependability and performance and how to measure them. |
Block II. MONOPROCESSOR PARALELLISM | Chapter 1. PIPELINING Introduction to the integer datapath, floating point datapath and pipelining performance. Different type of hazards and how to avoid them and reduce their impact. Chapter 2. INSTRUCTION LEVEL PARALELLISM (ILP) Basic concepts, superpipelining and superescalar processors. Chapter 3. DATA LEVEL PARALLELISM (DLP) Vector processors |
Block III. MULTIPROCESSORS PARALELLISM | Chapter 1. MULTIPROCESSORS INTRODUCTION Basic concepts about multiprocessors and parallelism and the main architectural approaches. Chapter 2. CENTRALIZED SHARED MEMORY ARCHITECTURE Distribution of this type of architectures, main features, algorithms to ensure coherence and consistency and performance. Chapter 3. DISTRIBUTED SHARED-MEMORY AND DIRECTORY-BASED COHERENCE Description of architectural approaches, main features and problems. Shared memory, cache coherence. Distributed memory, low latency networks. Chapter 4. HETEROGENEOUS ARCHITECTURES Architectures based on FPGAs and GPUs. |
Planning |
Methodologies :: Tests | |||||||||
Class hours | Hours outside the classroom | Total hours | |||||||
Problem solving, classroom exercises | 12 | 18 | 30 | ||||||
Laboratory practicals | 28 | 56 | 84 | ||||||
Personal tuition | 1 | 0 | 1 | ||||||
Lecture | 16 | 16 | 32 | ||||||
Extended-answer tests | 3 | 0 | 3 | ||||||
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. |
Methodologies |
Description | |
Problem solving, classroom exercises | Formulation, analysis, resolution and debate of a problem or exercise related to the topic of the subject. |
Laboratory practicals | Practical application of the theory of a knowledge area in a particular context. Practical exercises in the different laboratories. |
Personal tuition | Time that each teacher has to speak to pupils and resolve their doubts. |
Lecture | Description of the contents of the subject. |
Personalized attention |
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Assessment |
Description | Qualification | ||
Laboratory practicals | Lab assignments must work properly, and the students might be required to do some exams in order to probe they did their own work. | 50% | |
Problem solving, classroom exercises | The student will have to solve several exercises during the semester. There will be a deadline for each exercise. | 0-10% | |
Extended-answer tests | Exams which will include essay questions and problems. | 50% | |
Other comments and second call | |||
The marks assigned to the exercises given during the semester will be that of one of them, chosen randomly. All the assignments must be submitted before the deadlines. Lab assignments will consist in developing software and must be finished in due times, and the students have to pass every single one. The lecturer will choose the assessment methodology for each lab assignment . To pass this subject, it is required that the student gets a minimum of 50% the maximum qualification in both, the lab assignments and in the exams. The sum of all the qualifications must be at least 50%. In the second call, only the failed parts (theory or practice) will be taken. Grades are not retained for subsequent courses. |
Sources of information |
Access to Recommended Bibliography in the Catalog ULE |
Basic |
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Complementary |
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Recommendations |
Subjects that it is recommended to have taken before | ||
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