Practical Parallel Programming

• 26 hrs lectures
• 16 hrs pc labs
• 10 hrs projects

• 80 pts final exam (written part)
• 20 pts projects

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.

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.

This course will take you into the area of high performance computing where a single computer is far from being powerful enough to satisfy application demands. The only solution in such cases is to distribute computation across a supercomputing cluster. This course first examines the architecture of top machines, and then focuses on their software equipment. We will learn the MPI library which is an industry standard in high performance computing. Finally, we will introduce a few typical applications ranging such as physical simulation of heat distribution, fluid dynamics, n-body gravitational and Coulomb systems of galaxies and molecules or Monte-Carlo methods. 

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.

• MPI Tutoriál: http://mpitutorial.com/
• Alternativní kurz o paralelním programování http://www.cs.kent.edu/~jbaker/ParallelProg-Sp11/

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

1. MPI: Point-to-point communications
2. MPI: Collective communications
3. MPI: Communicators
4. MPI: Data types, reduction
5. MPI: Parallel input and output
6. Profiling and tracing of parallel applications
7. Matrix calculations.
8. Finite difference methods.

• A parallel program in MPI on the supercomputer.

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.

• 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.

To get 20 out of 40 points for projects and midterm examination.