- Jiří Kašpar
- Jiří Kašpar
- Department of Computer Systems
Students understand architecture of systems based on multicore processors with multiple threads per core, structure and usage of cache hierarchy with shared last level. They learn parallel algorithm classification, parallel programming technics, simulation and monitoring tools for measurement and optimization of parallel algorithms. After this course, students can design MTMD programs (Multiple Threads Multiple Data), measure and analyze latency and throughput of parallel algorithms and optimize them for contemporary multicore systems.
1. programming skills (assembler, C/C++ or C#),
2. OS Linux/Windows, networking,
3. BI-EIA, MI-PAP and MI-PAR are advantageous, but not strictly required.
- Syllabus of lectures:
1.Multiprocessor systems, multicore processors, multithreaded processor cores. Hierarchy of caches in multicore processor, cache coherency protocols.
2.Synchronization primitives and data consistency in multiprocessor systems, memory models.
3.Parallel programming patterns for MTMD model, parallel data structures and algorithms and their behavior and optimization on multicore systems with multiple cache layers (cache conscious programming).
4.Methods of parallel algorithms measurement and optimization.
5.Parallel methods properties: deadlock-free, starvation-free, lock-free, wait-free.
6.Operating system impact on parallel program performance and its elimination. Critical path and its optimization.
- Syllabus of tutorials:
1.Tutorial: Measurement of Intel cache hierarchy base properties.
2.Tutorial: Simulation of simple parallel algorithms.
3.Project assignment: measurement, simulation, evaluation and optimization of parallel algorithms.
5.Consultation. The 1st project checkpoint.
7.The 1st project results.
8.Consultation. Sponsors project assignment.
9.Consultation. The 2nd project checkpoint.
12.The 2nd project results.
13.The sponsors project results.
- Study Objective:
- Study materials:
1.Maurice Herlihy, Nir Shavit: The Art of Multiprocessor Programming.
2.Rauber, Thomas and Rünger, Gudula: Parallel Programming Models, Springer, 2010
3.David A. Patterson, John L. Hennessy: Computer Organization and Design: The Hardware/Software Interface, Fourth Edition
4.Ricardo Bianchini, Enrique V. Carrera and Leonidas Kontothanassis: Evaluating the Effect of Coherence Protocols on the Performance of Parallel Programming Constructs, 1998
5.Ricardo Bianchini, Leonidas Kontothanassis: Algorithms for Categorizing Multiprocessor Communication Under Invalidate and Update-Based Coherence Protocols, 1995
6.Bryan R. Buck,Jeffrey K. Hollingsworth: Using Hardware Performance Monitors to Isolate Memory Bottlenecks, 2000
- Further information:
- No time-table has been prepared for this course
- The course is a part of the following study plans:
- Knowledge Engineering, in Czech, Presented in Czech, Version 2016 and and 2017 (elective course)
- Computer Security, Presented in Czech, Version 2016 to 2019 (elective course)
- Computer Systems and Networks, Presented in Czech, Version 2016 to 2019 (elective course)
- Design and Programming of Embedded Systems, in Czech, Version 2016 to 2019 (elective course)
- Specialization Web and Software Engineering, in Czech, Version 2016 to 2019 (elective course)
- Specialization Software Engineering, in Czech, Version 2016 to 2019 (elective course)
- Specialization Web Engineering, Presented in Czech, Version 2016 to 2019 (elective course)
- Master Informatics, Presented in Czech, Version 2016 to 2019 (elective course)
- Specialization System Programming, Presented in Czech, Version 2016 to 2019 (elective course)
- Specialization Computer Science, Presented in Czech, Version 2016-2017 (elective course)
- Specialization Computer Science, Presented in Czech, Version 2018 to 2019 (elective course)
- Knowledge Engineering, in Czech, Presented in Czech, Version 2018 to 2019 (elective course)