Subject » BMEVIIIMA06
High Performance Parallel Computing
Nagyteljesítményű párhuzamos feldolgozás
A tantárgyleírás hatályossága
Hatályosság kezdete:
2026. March 21.
Hatályosság vége:
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| Subject name (Hungarian, English) |
Nagyteljesítményű párhuzamos feldolgozás
High Performance Parallel Computing
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| Subject code | BMEVIIIMA06 | ||||||||||||
| Subject type | — | ||||||||||||
| Training Level | — | ||||||||||||
| Course types and hours (weekly/semester) |
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| Assessment type | vizsga | ||||||||||||
| Credits | 4 | ||||||||||||
| Subject coordinator |
Dr. Szeberényi Imre
position: egyetemi docens
contact:
szeberenyi.imre@vik.bme.hu
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| Responsible department |
Irányítástechnika és Informatika Tanszék
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| Faculty | Villamosmérnöki és Informatikai Kar | ||||||||||||
| Subject website | iit.bme.hu | ||||||||||||
| Primary curriculum type | — | ||||||||||||
| Direct prerequisites – Strong prerequisite | none | ||||||||||||
| Direct prerequisites – Weak prerequisite | none | ||||||||||||
| Direct prerequisites – Parallel prerequisite | none | ||||||||||||
| Direct prerequisites – Milestone prerequisite | none | ||||||||||||
| Direct prerequisites – Exclusion | none |
Objectives
Programme
1. Historical overview. Needs of parallelisation. Basic concepts and classification of parallel architectures. Flynn Model Performance Measurement and Metrics, Benchmarks. Key features of HTC and HPC systems.
2. Levels of parallelisation (bit, instruction, pointer). The ideal model of the parallel computer. Architectures and models of parallel computers.
3. Practice: Classification and main features of parallel specific HPC systems available on the market and in the academic sphere. TOP 500 review, trends.
4. Task / Channel Model and Messaging Based Solutions. PRAM model, algorithm analysis.
5. Parallel Algorithm Design, Methods (PCAM).
6. Practice: Parallel Random Access Machine (PRAM) model and Partitioning Communication Agglomeration Mapping (PCAM) method examples.
7. Exercise Classes. Master-worker, pipeline, task, loop.
8. Programming models. Programming languages, environments (Linda, MPI).
9. Practice: Sample program in an MFI environment.
10. POSIX threads, OpenMP.
11. Accelerating processors, accelerator cards and their devices (GPGPU, ClearSpeed, Phi).
12. Practice: Paralleling cycles. Presentation of sample examples. Practical examples of SMP architecture.
13. Importance and portability of mathematical libraries. Simpler algorithms. Getting to know the Thrust and cuSPARSE libraries.
14. Schedules and distributed file systems.
15. Practice: BLAS, CUBLAS, MKL libraries with practical examples. It's a simple task using Thrust.
16. Paralleling existing codes. Performance Optimization Options. Code Review. Surprising power factors. Cache effect.
17. Profiling tools. Modern Processors Profiling Support Mechanisms. Check-point methods, problems and solutions.
18. Practice: Presentation of a specific profiling tool.
19. Meta-computing, Grid computing, Cloud and HPC / HTC relationship.
20. Summary
The course
introduces the architectural classes of supercomputers that require high-performance
computing or simulation and research tasks, as well as the software components
and programming languages required for their operation and application. The
students of the subject can get acquainted with the network solutions that are
used in the most powerful machines (TOP500). Also, they can get acquainted with
various accelerators and storage solutions. An important goal of the subject is
to provide a comprehensive view of the use, programming, quality control and
operation of these systems.
Learning outcomes
Ez a tantárgy a KKK rendeletben meghatározott, következő kompetenciák fejlesztését szolgálja:
Knowledge
No learning outcomes recorded.
Skills
No learning outcomes recorded.
Attitudes
No learning outcomes recorded.
Autonomy and responsibility
No learning outcomes recorded.
Oktatási módszertan
The course has theoretical and practical classes. The practical lessons, which are held every two weeks, are presented in practice with
the help of a sample program. We have several student seminars, which provides an opportunity to follow the fast-changing subject.
Tanulástámogató anyagok
Not provided.
Recommended preliminary knowledge for completing the subject
Knowledge type competencies
(azon előzetes ismeretek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
Programming, data structures, algorithms, mathematics, operating systems
Skill type competencies
(azon előzetes képességek és készségek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
nincs
Recommended (non-compulsory) preliminary competencies
(azon ajánlott (nem kötelező) előzetesen megszerzendő kompetenciák összessége, amelyek jelentősen hozzájárulnak a tantárgy eredményes teljesítéséhez)
Programming, data structures, algorithms, mathematics, operating systems
General rules
Requirements:
a.) Semester period: During the semester, attendance is checked at several unexpected times during the semester, and no signatures can be obtained for those who have missed more than 30% of the hours. At the pre-announced times, at least 4 control papers will be written and at the 12th week of study (at a pre-agreed time), a large closed class will be written. The writing of the test papers is not mandatory, they make the offer of tickets possible.b.) Homework: The big homework will be released on week 8, and the solution will be electronically uploaded at the latest before the exam day and presented in the exam. c.) Signature: You can only get a signature who has attended at least 70% of the lessons, and has completed at least a sufficient number of high locks. d) Exam: The exam is written and oral. The oral part is about presenting the homework and answering the questions about the task. The best 3 supervisor papers on the average reach the 85% level and the high closure result was outstanding and the homework was presented and finished by the end of the term. Qualified, Certified Exam Certificate.
Assessment methods
In-term assessments
No detailed assessments provided.
Weight of in-term assessments
No weights provided.
Exam-period assessments
No detailed assessments provided.
Weight of exam elements
No weights provided.
Grade calculation
No grade thresholds provided.
Attendance requirements
No attendance requirements provided.
Rules for retake and resubmission
Not provided.
Short description
Not provided.
Detailed description
Not provided.
Recommended courses
C or C++ programming knowledge is required to complete the course.
Workload to complete the subject
No workload breakdown provided.
Validity of subject requirements
Requirements valid from:
—
Requirements valid until:
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Curriculum placement
No curriculum placements recorded for this subject version.