Parallelism

Credits
6
Types
Compulsory
Requirements
  • Prerequisite: AC
Department
AC
The subject Parallelism covers the fundamental aspects related to parallel programming, a basic tool today to take advantage of the multi-core architectures that constitute current computers. The course includes a description of the main strategies for task and data decomposition, as well as the mechanisms to ensure its correctness (synchronization, mutual exclusion, ...) and ways to improve their performance.

Teachers

Person in charge

  • Daniel Jimenez Gonzalez ( )

Others

  • Adrián Munera Sánchez ( )
  • Eduard Ayguadé Parra ( )
  • Gladys Miriam Utrera Iglesias ( )
  • Jordi Tubella Murgadas ( )
  • Jose Ramon Herrero Zaragoza ( )
  • Lluc Álvarez Martí ( )
  • Mario Cesar Acosta Cobos ( )
  • Pedro José Martínez Ferrer ( )
  • Rosa Maria Badia Sala ( )

Weekly hours

Theory
2
Problems
0
Laboratory
2
Guided learning
0.4
Autonomous learning
5.6

Competences

Technical Competences

Common technical competencies

  • CT1 - To demonstrate knowledge and comprehension of essential facts, concepts, principles and theories related to informatics and their disciplines of reference.
    • CT1.1B - To demonstrate knowledge and comprehension about the fundamentals of computer usage and programming. Knowledge about the structure, operation and interconnection of computer systems, and about the fundamentals of its programming.
  • CT5 - To analyse, design, build and maintain applications in a robust, secure and efficient way, choosing the most adequate paradigm and programming languages.
    • CT5.1 - To choose, combine and exploit different programming paradigms, at the moment of building software, taking into account criteria like ease of development, efficiency, portability and maintainability.
    • CT5.3 - To design, write, test, refine, document and maintain code in an high level programming language to solve programming problems applying algorithmic schemas and using data structures.
    • CT5.6 - To demonstrate knowledge and capacity to apply the fundamental principles and basic techniques of parallel, concurrent, distributed and real-time programming.
  • CT6 - To demonstrate knowledge and comprehension about the internal operation of a computer and about the operation of communications between computers.
    • CT6.2 - To demonstrate knowledge, comprehension and capacity to evaluate the structure and architecture of computers, and the basic components that compound them.
  • CT7 - To evaluate and select hardware and software production platforms for executing applications and computer services.
    • CT7.2 - To evaluate hardware/software systems in function of a determined criteria of quality.
  • CT8 - To plan, conceive, deploy and manage computer projects, services and systems in every field, to lead the start-up, the continuous improvement and to value the economical and social impact.
    • CT8.1 - To identify current and emerging technologies and evaluate if they are applicable, to satisfy the users needs.

Transversal Competences

Third language

  • G3 [Avaluable] - To know the English language in a correct oral and written level, and accordingly to the needs of the graduates in Informatics Engineering. Capacity to work in a multidisciplinary group and in a multi-language environment and to communicate, orally and in a written way, knowledge, procedures, results and ideas related to the technical informatics engineer profession.
    • G3.2 - To study using resources written in English. To write a report or a technical document in English. To participate in a technical meeting in English.

Objectives

  1. Ability to formulate simple performance models given a parallelization strategy for an application, that allows an estimation of the influence of major architectural aspects: number of processing elements, data access cost and cost of interaction between processing elements, among others.
    Related competences: CT7.2,
  2. Ability to measure, using instrumentation, visualization and analysis tools, the performance achieved with the implementation of a parallel application and to detect factors that limit this performance: granularity of tasks, equitable load and interaction between tasks, among others.
    Related competences: CT7.2,
  3. Ability to compile and execute a parallel program, using the essential command-line tools to measure the execution time.
    Related competences: CT7.2, CT5.3,
  4. Ability to apply simple optimizations in parallel kernels to improve their performance for parallel architectures, attacking the factors that limit performance.
    Related competences: CT7.2, CT6.2,
  5. Ability to choose the most appropriate decomposition strategy to express parallelism in an application (tasks, data).
    Related competences: CT5.1,
  6. Ability to apply the basic techniques to synchronize parallel execution, avoiding race conditions and deadlock and enabling the overlap between computation and interaction, among others.
    Related competences: CT5.1,
  7. Ability to program in OpenMP the parallel version of a sequential application.
    Related competences: CT5.3, CT5.6,
  8. Ability to identify the different types of parallelism that can be exploited in a computer architecture (ILP, TLP, and DLP within a processor, multiprocessor and multicomputer) and describe its principles of operation.
    Related competences: CT8.1, CT6.2, CT1.1B,
  9. Ability to understand the basics of coherence and data sharing in shared-memory parallel architectures, both with uniform and non-uniform access to memory.
    Related competences: CT8.1, CT6.2, CT1.1B,
  10. Ability to follow the course using the materials provided in English (slides, laboratory and practical sessions), as well as to do the mid-terms and final exams with the statement written in English.
    Related competences: G3.2,
  11. If the foreign language competence is chosen, the ability to write the deliverables associated with laboratory assignments (partially or fully) in English.
    Related competences: G3.2,

Contents

  1. Introduction and motivation
    Necessitat del paral.lelisme, paral.lelisme vs. concurrència, possibles problemes en l'us concurrència: deadlock, lifelock, starvation, fairness, data races
  2. Analysis of parallel applications
    Mètriques bàsiques: paral·lelisme, temps d'execució, speedup i escalabilitat. Análisi de l'impacte dels overheads associats a la creació de tasques i la seva sincronització i la compartició de dades. Eines per la predicció i l'anàlisi de paral.lelisme i visualització de comportament: Paraver i Tareador
  3. Shared-memory programming: OpenMP
    Regions paral.leles, threads i tasques. Mecanismes de sincronització entre tasques i threads. Distribució de feina estàtica/dinàmica, granularitat.
  4. Introduction to parallel architectures
    Paral.lelisme dins d'un processador (ILP, DLP i TLP) i entre els processadors que formen els multiprocessadors de memòria compartida SMP i ccNUMA (coherència de cache, consistència de memòria, sincronització).
  5. Parallel programming principles: task decomposition
    Task decomposition vs. data decomposition. Descomposcio en tasques, granularitat i anàlisi de dependències. Identificació de patrons de paral.lelisme: iterative vs. divide and conquer task decompositions. Mecanismes per implementar la descomposició en tasques: creació de regions paral·leles i tasques; mecanismes per garantir task ordering i data sharing.
  6. Parallel programming principles: data decomposition
    Descomposició de dades (descomposició geomètrica vs. estructures recursives) per arquitectures amb memoria compartida. Localitat en l'accés a les dades en arquitectures paral·leles de memòria compartida. Generació de codi en funció de la descomposició de dades. Breu introducció a les arquitectures de memòria distribuïda i la seva programació (cas concret: MPI).
  7. Exam problems review
    En aquestes sessions es resoldran dubtes que l'estudiantat pugui tenir alhora de resoldre problemes d'examens.

Activities

Activity Evaluation act


Assimilation of fundamental concepts and tools for modeling and analyzing the behavior of parallel applications

Actively participate in sessions of theory/problems. Study the contents of Units 1 and 2 and perform the proposed exercises. Resolution of the assignments in the laboratory sessions and understanding of the obtained results.
Objectives: 1 3 2 10
Contents:
Theory
6h
Problems
0h
Laboratory
6h
Guided learning
0h
Autonomous learning
6h

Using OpenMP to express of parallelism in shared memory

Actively participate in laboratory sessions. Do the suggested previous work/reading, solve the exercises during the laboratory sessions, analyse the obtained results, draw conclusions from the experiments and prepare the corresponding deliveries.
Objectives: 4 7 10 11
Contents:
Theory
0h
Problems
0h
Laboratory
22h
Guided learning
0h
Autonomous learning
22h

Assimilation of the fundamental aspects in parallel architectures

Actively participate in sessions of theory/problems. Study the contents of Unit 4 and perform the proposed exercises.
Objectives: 8 10
Contents:
Theory
6h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
6h

Midterm exam


Objectives: 9 1 5 6 7 10
Week: 7
Type: theory exam
Theory
2h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
10h

Assimilation of the fundamentals for task decomposition

Actively participate in sessions of theory/problems. Study the contents of Unit 5 and perform the proposed exercises. Apply new knowledge when solving the associated laboratory assignments.
Objectives: 5 6 10
Contents:
Theory
8h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
10h

Assimilation of the fundamentals for data decomposition

Actively participate in sessions of theory/problems. Study the contents of Unit 6 and perform the proposed exercises. Apply new knowledge when solving the associated laboratory assignments.
Objectives: 5 6 10
Contents:
Theory
8h
Problems
0h
Laboratory
0h
Guided learning
0h
Autonomous learning
10h

Midterm problems review

Study the solution proposed for the problems in the mid-term exam and contrast it with the solution delivered. Discussion of the differences observed.
  • Guided learning: Carrying out practical activities, aimed at small groups, on other programming models
Objectives: 9 10
Contents:
Theory
0h
Problems
0h
Laboratory
0h
Guided learning
3h
Autonomous learning
4h

Final exam


Objectives: 8 9 4 5 6 7 10
Week: 15 (Outside class hours)
Type: final exam
Theory
0h
Problems
0h
Laboratory
0h
Guided learning
3h
Autonomous learning
16h

Teaching methodology

The theory classes introduce all the knowledge, techniques, concepts needed to be put into practice problems in class and lab as well as personal work using a collection of problems. The two hours of laboratory sessions are also held weekly; active participation and performance during the laboratory sessions will be valued (work during the session, advancing as far as possible in order to achieve the objectives of each session). The course uses the C programming language and the OpenMP parallel programming model.

Evaluation methodology

The grade for the course (NF) is calculated based on the following components (all assessed out of 10):
- P: the mark of the mid-term exam (includes Units 1 to 3)
- F: the mark in the final exam (Units 1 to 5)
- L: the laboratory mark
- AA: the mark of the online activities via Atenea carried out within the established period

applying the following weighting:
N = 0,75*max(F, 0,35*P+0,65*F) + 0,25*L
If N>=5,0 then NF = MIN(10, N * (1 + AA/100)); NF=N otherwise.

The laboratory mark (L) is obtained from the grades obtained in the deliverables, modulated by the attendance to the laboratory sessions, the active participation and performance and the result of a possible interview at the end of the course. By active participation, we refer to the reliable demonstration of being working on the laboratory assignment, advancing as far as possible to achieve each session's objectives.

The foreign language competence will be evaluated from the reports delivered for the laboratory assignments. These reports should be written (partially or fully) in English and they will require reading the laboratory assignment description (also in English) as well as the OpenMP specifications. Both the structure of the written document and the ability to transmit the results and conclusions of the work will be used to evaluate the competence (following a rubrics document). The grade for the competence will be A (excellent), B (good), C (satisfactory), D (fail) or NA (Not evaluated).

Bibliography

Basic:

Complementary:

  • Parallelism - Unit 1: Why Parallel Computing - Eduard Ayguade, Josep Ramon Herrero, Daniel Jimenez and Gladys Utrera, Departament d'Arquitectura de Computadors , 2022.
  • Parallelism - Unit 2: Understanding Parallelism - Eduard Ayguade, Josep Ramon Herrero, Daniel Jimenez and Gladys Utrera, Departament d'Arquitectura de Computadors , 2022.
  • Parallelism - Unit 3: Introduction to parallel architectures - Eduard Ayguade, Josep Ramon Herrero, Daniel Jimenez and Gladys Utrera, Departament d'Arquitectura de Computadors , 2022.
  • Parallelism - Unit 4: Mastering your task decomposition strategies: going some steps further - Eduard Ayguade, Josep Ramon Herrero, Daniel Jimenez and Gladys Utrera, Departament d'Arquitectura de Computadors , 2022.
  • Parallelism - Unit 5: Data-aware task decomposition strategies - Eduard Ayguade, Josep Ramon Herrero, Daniel Jimenez and Gladys Utrera, Departament d'Arquitectura de Computadors , 2022.
  • Parallelism: Collection of Exercises - Eduard Ayguade, Josep Ramon Herrero, Daniel Jimenez and Gladys Utrera, Departament d'Arquitectura de Computadors , 2022.
  • Parallelism: Selection of Exams (with Solutions) - Eduard Ayguade, Josep Ramon Herrero, Daniel Jimenez and Gladys Utrera, Departament d'Arquitectura de Computadors , 2022.
  • Parallelism Laboratory Assignments - Eduard Ayguadé et al., Departament d'Arquitectura de Computadors , 2022.
  • Computer architecture: a quantitative approach - Hennessy, J.L.; Patterson, D.A, Elsevier, Morgan Kaufmann , 2019. ISBN: 9780128119051
    https://discovery.upc.edu/discovery/fulldisplay?docid=alma991004117509706711&context=L&vid=34CSUC_UPC:VU1&lang=ca
  • Parallel computer architecture: a hardware/software approach - Culler, D.E.; Singh, J.P.; Gupta, A, Morgan Kaufmann Publishers , 1999. ISBN: 9781558603431
    https://discovery.upc.edu/discovery/fulldisplay?docid=alma991001862689706711&context=L&vid=34CSUC_UPC:VU1&lang=ca

Previous capacities

The capabilities are defined by the prior pre-requisites for the course.