Course detail
Practical Parallel Programming
FIT-PPPAcad. year: 2023/2024
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
Number of ECTS credits
Mode of study
Guarantor
Department
Entry knowledge
Von-Neumann computer architecture, computer memory hierarchy, cache memories and their organization, programming in C/C++. Knowledge gained in courses PRL and AVS.
Rules for evaluation and completion of the course
Assessment of a project, 10 hours in total and a midterm examination.
- 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.
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.
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.
Study aids
Prerequisites and corequisites
Basic literature
Ananth Grama, Anshul Gupta, George Karypis, Vipin Kumar: Introduction to Parallel Computing, Addison-Wesley, 2003, 978-0201648652.Slides: download
Hennessy, J.L., Patterson, D.A.: Computer Architecture - A Quantitative Approach. 5. vydání, Morgan Kaufman Publishers, Inc., 2012, 1136 s., ISBN 1-55860-596-7.
Pacecho, P.: Introduction to Parallel Programming. Morgan Kaufman Publishers, 2011, 392 s., ISBN: 9780123742605 URL: download
Victor Eijkhout: Parallel Programming in MPI and OpenMP Full book: download web version: https://theartofhpc.com/pcse/
William Gropp, Ewing Lusk, Anthony Skjellum: Using MPI - 2nd Edition: Portable Parallel Programming with the Message Passing InterfaceUsing MPI - 2nd Edition: Portable Parallel Programming with the Message Passing Interface, MIT Press, 978-0262571326
Recommended reading
MPI Tutoriál: http://mpitutorial.com/
Elearning
Classification of course in study plans
- Programme IT-MSC-2 Master's
branch MGM , 0 year of study, summer semester, compulsory-optional
branch MBI , 0 year of study, summer semester, compulsory-optional
branch MBS , 0 year of study, summer semester, elective
branch MPV , 1 year of study, summer semester, compulsory
branch MIS , 0 year of study, summer semester, elective
branch MIN , 0 year of study, summer semester, elective
branch MSK , 1 year of study, summer semester, compulsory
branch MMM , 0 year of study, summer semester, elective - Programme MITAI Master's
specialization NISY , 0 year of study, summer semester, elective
specialization NSPE , 0 year of study, summer semester, elective
specialization NBIO , 0 year of study, summer semester, compulsory
specialization NSEN , 0 year of study, summer semester, elective
specialization NVIZ , 0 year of study, summer semester, elective
specialization NGRI , 0 year of study, summer semester, elective
specialization NADE , 0 year of study, summer semester, elective
specialization NISD , 0 year of study, summer semester, elective
specialization NMAT , 0 year of study, summer semester, elective
specialization NSEC , 0 year of study, summer semester, elective
specialization NISY up to 2020/21 , 0 year of study, summer semester, elective
specialization NCPS , 0 year of study, summer semester, elective
specialization NHPC , 1 year of study, summer semester, compulsory
specialization NNET , 0 year of study, summer semester, elective
specialization NMAL , 0 year of study, summer semester, elective
specialization NVER , 0 year of study, summer semester, elective
specialization NIDE , 0 year of study, summer semester, elective
specialization NEMB , 2 year of study, summer semester, compulsory
specialization NEMB up to 2021/22 , 2 year of study, summer semester, compulsory
Type of course unit
Lecture
Teacher / Lecturer
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
Teacher / Lecturer
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
Teacher / Lecturer
Syllabus
- A parallel program in MPI on the supercomputer.
Elearning