Main page | Study Branches/Specializations | Groups of Courses | All Courses | Roles                Instructions

A course is the basic teaching unit, it's design as a medium for a student to acquire comprehensive knowledge and skills indispensable in the given field. A course guarantor is responsible for the factual content of the course.
For each course, there is a department responsible for the course organisation. A person responsible for timetabling for a given department sets a time schedule of teaching and for each class, s/he assigns an instructor and/or an examiner.
Expected time consumption of the course is expressed by a course attribute extent of teaching. For example, extent = 2 +2 indicates two teaching hours of lectures and two teaching hours of seminar (lab) per week.
At the end of each semester, the course instructor has to evaluate the extent to which a student has acquired the expected knowledge and skills. The type of this evaluation is indicated by the attribute completion. So, a course can be completed by just an assessment ('pouze zápočet'), by a graded assessment ('klasifikovaný zápočet'), or by just an examination ('pouze zkouška') or by an assessment and examination ('zápočet a zkouška') .
The difficulty of a given course is evaluated by the amount of ECTS credits.
The course is in session (cf. teaching is going on) during a semester. Each course is offered either in the winter ('zimní') or summer ('letní') semester of an academic year. Exceptionally, a course might be offered in both semesters.
The subject matter of a course is described in various texts.

MI-PRC Programming in CUDA Extent of teaching: 2P+1C
Instructor: Completion: Z,ZK
Department: 18104 Credits: 4 Semester: L

Annotation:
The students gain a good overview of present parallel architectures in GPUs. Students also get hands-on experience with programming these systems.

Lecture syllabus:
1. Introduction, system of classification
2. Multithreaded programming
3. Introduction to GPGPU
4. Introduction of CUDA API
5. CUDA datatypes
6. Synchronization of threads and blocks
7. Textures and streams
8. CUDA optimization - SIMT architecture, coalesced memory access pattern
9. CUDA optimization - transformations of source codes
10. CUDA API libraries
11. CUDA and other programming languages
12. Overview of other API for GPGPU
13. Final prezentation, conclusions

Seminar syllabus:
1. Introduction, assigning projects to students
2. Serial project presentation
3. CUDA code compilation, linking CUDA libraries
4. Debugging and profiling tools
5. Project consultation
6. CUDA project presentation, assessment

Literature:
J. Sanders, E. Kandrot ''CUDA by Example: An Introduction to General-Purpose GPU Programming''
David B. Kirk, Wen-mei W. Hwu: Programming Massively Parallel Processors: A Hands-on Approach. 1st ed., Morgan Kaufmann, 2010.

Requirements:
Programming in C/C++, parallel algorithms, computer architectures.

Informace o předmětu a výukové materiály naleznete na https://courses.fit.cvut.cz/MI-PRC/

The course is also part of the following Study plans:
Study Plan Study Branch/Specialization Role Recommended semester
MI-ZI.2016 Knowledge Engineering V Není
MI-ZI.2018 Knowledge Engineering V Není
MI-SP-TI.2016 System Programming V Není
MI-SP-SP.2016 System Programming V Není
MI-SPOL.2016 Unspecified Branch/Specialisation of Study V Není
MI-WSI-WI.2016 Web and Software Engineering V Není
MI-WSI-SI.2016 Web and Software Engineering V Není
MI-WSI-ISM.2016 Web and Software Engineering V Není
MI-NPVS.2016 Design and Programming of Embedded Systems V Není
MI-PSS.2016 Computer Systems and Networks V Není
MI-PB.2016 Computer Security V Není
NI-TI.2018 Computer Science V 2
MI-WSI-ISM.2016 Web and Software Engineering V 6


Page updated 28. 3. 2024, semester: Z/2023-4, L/2019-20, L/2022-3, Z/2019-20, Z/2022-3, L/2020-1, L/2023-4, Z/2020-1, Z,L/2021-2, Send comments to the content presented here to Administrator of study plans Design and implementation: J. Novák, I. Halaška