Course detail

Practical Parallel Programming

FIT-PPPAcad. year: 2019/2020

The course covers architecture and programming of parallel systems with functional and data parallelism. First, the parallel system theory and program parallelization are discussed. The detailed description of most proliferated supercomputing systems, interconnection network typologies and routing algorithms is followed by the architecture of parallel and distributed storage systems. The course goes on in message passing programming in standardized interface MPI. Consequently, techniques for parallel debugging and profiling are discussed. Last part of the course is devoted to the description of parallel programming patterns and case studies from the are of linear algebra, physical systems described by partial differential equations, N-Body systems and Monte-Carlo methods.

Language of instruction

Czech

Number of ECTS credits

Mode of study

Not applicable.

Guarantor

doc. Ing. Jiří Jaroš, Ph.D.

Department

Department of Computer Systems (UPSY)

Learning outcomes of the course unit

Overview of principles of current parallel system design and of interconnection networks, communication techniques and algorithms. Survey of parallelization techniques of fundamental scientific problems, knowledge of parallel programming in MPI. Knowledge of basic parallel programming patterns. Practical experience with the work on supercomputers, ability to identify performance issues and propose their solution.
Knowledge of capabilities and limitations of parallel processing, ability to estimate performance of parallel applications. Language means for process/thread communication and synchronization. Competence in hardware-software platforms for high-performance computing and simulations.

Prerequisites

Von-Neumann computer architecture, computer memory hierarchy, cache memories and their organization, programming in assembly and in C/C++. Knowledge gained in courses PRL and AVS.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Assessment of a project, 10 hours in total and a midterm examination.
Exam prerequisites:
To get 20 out of 40 points for projects and midterm examination.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

To get familiar with the architecture of distributed supercomputing systems, their interconnection networks and storage. To orientate oneself in parallel systems on the market, be able to assess communication and computing possibilities of a particular architecture and to predict the performance of parallel applications. Learn how to write portable programs using standardized interfaces and languages, specify parallelism and process communication. To learn how to practically use supercoputer for solving complex engineering problems.

Specification of controlled education, way of implementation and compensation for absences

Missed labs can be substituted in alternative dates (monday or friday)
There will be a place for missed labs in the last week of the semester.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Type of course unit

Lecture

26 hours, optionally

Teacher / Lecturer

doc. Ing. Jiří Jaroš, Ph.D.

Syllabus

Introduction to parallel processing.
Architectures with distributed memory,
Interconnection networks: topology and routing algorithms, switching, flow control.
Technologies of interconnection networks (Infiniband).
Distributed file systems (Lustre, HPFS).
Message passing interface, pair-wise communications, data types
Collective communications and communicators,
Hybrid programming OpenMP/MPI and one-sided communications.
Parallel code debugging, profiling and tracing.
Programming patterns for parallel programming.
Case studies: matrix calculations, linear equation systems
Case studies: solution of PDE systems, finite difference, spectral methods
Case studies: Fluid dynamics, N-Body systems, Monte-Carlo.

Exercise in computer lab

16 hours, compulsory

Teacher / Lecturer

Ing. Filip Vaverka, Ph.D.

Syllabus

MPI: Point-to-point communications
MPI: Collective communications
MPI: Communicators
MPI: Data types, reduction
MPI: Parallel input and output
Profiling and tracing of parallel applications
Matrix calculations.
Finite difference methods.

Project

10 hours, compulsory

Teacher / Lecturer

Ing. Filip Vaverka, Ph.D.

Syllabus

A parallel program in MPI on the supercomputer.

VUT

Faculties

University Institutes

Parts

Practical Parallel Programming

Type of course unit