The final grade will be the weighted addition of the mixed test and the laboratory practice grades. In order to pass it is necessary to get at least 50% of the maximum grade. If a grade of 50% or more is achieved but some of the necessary conditions for passing the mixed test and laboratory practice are not met the final grade will be FAIL (4.5).

For the July evaluation only the mixed test will be graded again (70% of the total grade). It is still necessary to get at least 40% of the maximum grade in this exam.

The grade obtained during the term in the laboratory practice (30% of the final grade) will be used for both the June and July evaluations. The evaluation of the laboratoy practice must be done in the group assigned to each student.

No special consideration will be given to students with part time enrollment.

Learning outcomes	Study programme competences
The student should know basic algorithms and how to apply them to solve problems, analyzing the adequacy and complexity of the proposed concurrent and parallel algorithms.	A12	B3	C4
The student should know how to apply the fundamentals of real time, parallel, concurrent and distributed programming.	A20		C6 C8

Topic	Sub-topic
T1. Concurrent programming fundamentals	1.1 Concepts 1.1.1 Hardware architectures 1.1.2 Operating Systems 1,1.3 Threads and Processes 1.2 Multiprocess programming (fork/join) 1.3 Multithread programming 1.4 Critical section 1.5 Mutual exclusion 1.6 Atomic instructions 1.7 Condition synchronization 1.8 Semaphores 1.8.1 Mutex 1.8.2 Semaphores 1.9 Deadlock. Prevention, avoidance, recovery 1.10 Starvation 1.11 Communication and synchronization 1.12 Scalability
T2. Concurrent Algorithms	2.1 Producers/consumers. 2.2 Readers/writers 2.3 Dining philosophers 2.4 Shared nothing
T3. Parallel programming principles	3.1 Concepts 3.1.1 Levels of paralellism 3.1.2 Data dependencies 3.2 Message passing model 3.2.1 Basic concepts 3.2.2 Point to point communication 3.2.3 Collective operations 3.3 Analysis of parallel algorithms 3.3.1 Performance measure of parallel algorithms 3.4 Methodology for parallel programming 3.4.1 Task decomposition 3.4.2 Task assignment 3.4.3 Optimization techniques 3.5 Schemes for parallel algorithms 3.5.1 Single Process Multiple Data 3.5.2 Master/slave paradigm
T4. Design of parallel algorithms and applications	4.1 Message passing libraries 4.2 Case of study 4.3 Performance evaluation 4.4 Inclusion of optimization techniques

Methodologies / tests	Competencies	Ordinary class hours	Student’s personal work hours	Total hours
Guest lecture / keynote speech	A12 A20 C4 C6 C8	25	40	65
Mixed objective/subjective test	A12 A20 B3 C4 C6	3	0	3
Laboratory practice	A12 A20 B3 C8	16	24	40
Problem solving	B3 C6	10	20	30
Seminar	A12 A20 B3 C4 C6 C8	5	6	11

Personalized attention		1	0	1

(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies	Description
Guest lecture / keynote speech	Lecture with audiovisual reinforcement materials, and questions directed at the students to reinforce the transmission of concepts and improve the learning process.
Mixed objective/subjective test	Written exam with questions about the content of the lectures and the practical problems solved in the laboratory practice.
Laboratory practice	Practical activities aimed at enhancing the comprehension of the material by the students, such as programming exercicies.
Problem solving	Solving of concrete problems that appeared during the laboratory practice, possibly exploring multiple solutions.
Seminar	Presentation in groups about specific topics for in depth analysis, encouraging discussion and participation by everyone in attendance.

Methodologies	Competencies	Description	Qualification
Laboratory practice	A12 A20 B3 C8	Practical exercises divided on two blocks: concurrency and parallelism. Each block is worth 50% of the laboratory practice grade. Exercises can be solved in groups of two, but will be graded individually. It is necessary to get at least 50% of the grade of each block of the laboratory practice in order to pass the subject. If the grade of either block is less than 50% the student will fail the subject in the June evaluation. In this situation, and student who does the exam in June will get a FAIL grade (SUSPENSO). A student who does not do the exam in June will get a DID NOT REPORT (NO PRESENTADO).	30
Mixed objective/subjective test	A12 A20 B3 C4 C6	Exam on the contents explained during the lectures and practiced in the laboratory. There will be two parts: concurrency (topics T1 and T2) and parallelism (topics T3 and T4). Each part is worth 50% of the grade of the mixed test. In order to pass the subject it is necessary to get at least 40% of the maximum grade.	70

Assessment comments
The final grade will be the weighted addition of the mixed test and the laboratory practice grades. In order to pass it is necessary to get at least 50% of the maximum grade. If a grade of 50% or more is achieved but some of the necessary conditions for passing the mixed test and laboratory practice are not met the final grade will be FAIL (4.5). For the July evaluation only the mixed test will be graded again (70% of the total grade). It is still necessary to get at least 40% of the maximum grade in this exam. The grade obtained during the term in the laboratory practice (30% of the final grade) will be used for both the June and July evaluations. The evaluation of the laboratoy practice must be done in the group assigned to each student. No special consideration will be given to students with part time enrollment.

Basic	Doug Lea (2000). Concurrent programming in Java design, principles and patterns . Reading, Massachusetts: Addison Wesley Francisco Almeida [et al.] (2008). Introducción a la Programación Paralela. Madrid: Paraninfo Cengage Learning Peter S. Pacheco (1997). Parallel Programming with MPI. San Francisco, California : Morgan Kauffman Joe Armstrong (2007). Programming Erlang: Software for a Concurrent World. United States: Pragmatic Programmers

Complementary	Wilkinson, B. y Allen, M.. (1999). Parallel Programming. Techniques and Applications Using Networked Workstations and Parallel Computers. . Upper Saddle River, New Jersey : Prentice Hall,

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