Degree | Type | Year | Semester |
---|---|---|---|
2503740 Computational Mathematics and Data Analytics | OB | 3 | 1 |
Although there are no formally established prerequisites and the subject will provide students with the means to acquire the knowledge described in the syllabus, it is advisable: a good knowledge of programming, of the computer structure, of the operating system at the level of user programmer and how messages are sent over the network (Fondations of Computers, System Software, Introduction to Programming)
The objective of this subject is to study high performance and parallel computing systems, multiprocessor and multicomputer systems, paradigms of parallel programming, learn to develop applications with shared memory, introduce the concept of message passing and applications in distributed memory, and analyze the performance of these applications.
The theoretical concepts about programming paradigms, shared memory and message passing, are reinforced with problem sessions and labs in which students learn to program using parallel programming languages.
All the components described in this subject should allow the student to understand the performance of high performance and parallel systems and, to a certain extent, be able to perform a simple design of a parallel application and evaluate its performance.
Topic 1: Introduction to high performance systems.
C advanced programming. Concurrency: definition, race conditions, critial region, and mutual exclusion mechanisms.
Introduction to high performance systems, parallel systems, multiprocessors and multicomputers. Execution of parallel applications in high performance systems.
Topic 2: Classification of parallelism
SIMD (Single Instruction, Multiple Data), MIMD (Multiple Instruction, Multiple Data). Models of parallel applications.
Topic 3: Parallel Algorithms
Definition of parallel algorithms. Examples of parallel algorithms. Development of parallel algorithms.
Topic 4: Parallel programming
Paradigms of parallel programming. Applications based on message passing. MPI standard (Message Passing Interface). Applications based on shared memory. Standards OpenMP (Open multiprocessing) and OpenACC (Open Accelerators). Parallelism in Python. Development of parallel applications using MPI, OpenMP, OpenACC and Python.
Topic 5: Performance Analysis
Performance analysis of parallel systems. Performance evaluation of parallel systems. Examples of performance evaluation tools.
During the development of the subject four types of teaching activities cam be differentiated:
This approach to work is oriented to promote an active learning and developing competencies of organization and planning skills, oral and written communication, teamwork and critical reasoning. The quality of the exercises carried out, their presentation and their functioning will be especially valued.
Variations in the teaching methodology due to the health situation present in 2020:
During the 1st semester of the 2020-21 academic year, it is planned that this subject will be done in a partial attendance regime.
Given the exceptional nature of this fact, the specific conditions under which the course will take place are not included in this guide. At the beginning of the course you will have a plan adapted to the circumstances, which may vary according to the events.
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Exercise Seminars | 11 | 0.44 | 1, 11, 3, 10, 2, 4, 9, 7, 6, 5 |
Labs | 10 | 0.4 | 1, 11, 3, 10, 2, 4, 7, 6, 5 |
Theory | 24 | 0.96 | 1, 3, 10, 9, 8, 5 |
Type: Autonomous | |||
Autonomous preparation | 30 | 1.2 | 1, 3, 10, 8, 7, 6, 5 |
Lab preparation | 30 | 1.2 | 1, 11, 3, 10, 2, 4, 7, 6, 5 |
Seminar preparation | 30 | 1.2 | 1, 11, 3, 10, 2, 4, 7, 6, 5 |
The objective of the assessment process is to verify that the student has achieved the knowledge and skills defined in the objectives of the subject, as well as the associated competences.
Four types of activities will be assessed independently, and the weighted sum of them will give the final grade. These activities are:
The part of Theory (T) will be evaluated with two individual written exams throughout the course. The final grade of Theory will come out of the weighted sum of the two examns (0.5 * Exam 1 + 0.5 * Exam 2). There will be a second chance to recover this part on the day we have assigned in the February exams week. The parts that have not been passed in the partial theory exams can be recovered. The minimum grade for passing this part is >= 4.5.
The part of Laboratory exercises (PL) will be evaluated by group. There number of deliveries will depend on the number of technologies introduced in the course. The final grade will come from the weighted sum of the deliveries (the number of deliveries and their weight in the evaluation will be informed at the beginning of the course). To pass the PL the minimum mark will have to be >= 4.5. There is only one opportunity to pass this part (this part can not be recovered).
The practical exercises (PA) will consist of solving very specific programming problems that will be relate in some cases to those that will be found in the laboratory exercices. It is expected that each student will focus in the resolution of a set of specific problems isolated from the most general case of the lab exercices. Given their nature and objective these exercices are not recoverable (not delivering an assignment or delivering after its deadline implies a 0 mark).
The final grade of the subject will be the weighted sum of the grades of each of the four activities: Theory,Resolution of individual practical exercises and Resolution of laboratory exercices. The result will have to be >= 5.
In case a student does not pass the subject due to not reaching the minimum score in any of the mandatory parts (Theory or Laboratory exercices), even though the weighted average is equal or superior to 5, the final grade of the subject will be 4.5.
In the event that the average does not reach 5, the official grade will be the average mark obtained numerically.
If the student delivers any activity, it is understood that he/she is participating in the subject and will be evaluated. If you do not deliver any activity, then it can be considered Non-evaluable.
Granting an honorific matriculation qualification is a decision of the faculty responsible for the subject. The regulations of the UAB indicate that MH can only be awarded to students who have obtained a final grade of 9.00 or more. It can be granted up to 5% of MH of the total number of students enrolled.
The dates of continuous evaluation and assignment delivery will be published on the virtual campus and may be subject to possible changes to adapt to possible incidents; the virtual campus will always inform about these changes since it is understood that the CV is the usual mechanism for exchanging information betweenprofessors and students.
For each assessment activity, a place, date and time of revision will be indicated in which the student will be able to review the activity with the professor. In this context, claims can be made about the activity grade, which will be evaluated by the professors responsible for the subject. If the student does not submit to this review, this activity will not be reviewed later.
SUMMARY
If ((T> = 4) i (P> = 4) then
NF = 0.35 * T + 0.25 * VA + 0.2 * PA + 0.40 * PL
If (NF> = 5) then PASS
elseFAIL
else FAIL
Repeating students: repeating students who have passed laboratory exercices in previous editions of the subject may request the validation of this part of the subject. The rest of the assessment activities must be carried out under the same conditions as the other students.
Note about plagiarism:
Without prejudice to other disciplinary measures deemed appropriate, and in accordance with the current academic regulations, irregularities committed by a student who maylead to a variation of the qualification in an assessable activity will be graded with zero (0). Assessment activities qualified in this way and by this procedure will not be recoverable. If it is necessary to pass any of these assessment activities to pass the subject, this subject will be suspended directly, without opportunity to recover it in the same course. These irregularities include, among others:
If you do not pass the subject due to the fact that some of the evaluation activities do not reach the minimum grade required, the numerical official grade will be the lowest value between 4.5 and the weighted average of the grades. With the exceptions that the "Non-Appraising" qualification will be awarded to students who do not participate in any of the assessment activities, and that the numerical official grade will be the lowest value between 3.0 and the average Weighted grades in case the student has committed irregularities in an evaluation act (and therefore the subject cannot beapproved by compensation). In future editions of this subject, the student who has committed irregularities in an evaluation act will not be validated any of the assessment activities carried out.
In summary: copy, let copy or plagiarize (or attempt) in any of the assessment activities will lead to a FAIL, not compensable and without validations of parts of the subject in subsequent courses.
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
1st Individual exam | 17.5% | 2 | 0.08 | 3, 4, 9, 8, 7, 6 |
2nd Individual exam | 17.5% | 2 | 0.08 | 1, 3, 10, 2, 9, 8, 7, 6 |
Exercises assessment | 25% | 6 | 0.24 | 1, 11, 3, 10, 2, 4, 6, 5 |
Laboratories | 40% | 5 | 0.2 | 1, 11, 3, 10, 2, 4, 8, 7, 6, 5 |