Course Manual PPRA
Parallel Programming and Computerarchitektur
PDF Course Catalog Deutsche Version: PPRA
Version: 3 | Last Change: 29.04.2022 08:41 | Draft: 2 | Status: Entwurf
| Long name | Parallel Programming and Computerarchitektur |
|---|---|
| Approving CModule | PPRA_BaTIN |
| Responsible |
Prof. Dr. Lothar Thieling
Professor Fakultät IME |
| Valid from | summer semester 2021 |
| Level | Bachelor |
| Semester in the year | summer semester |
| Duration | Semester |
| Hours in self-study | 60 |
| ECTS | 5 |
| Professors |
Lehrbeauftragte(r) / Thieling
|
| Requirements | basic skills in procedural programming basic skills in programming multiple tasks structure and mode of operation of a simple computer basics in digital systems (Automata, Hardware Description Language) |
| Language | German |
| Separate final exam | Yes |
Literature
| Barlas, Gerassimos: Multicore and GPU Programming: An Integrated Approach |
| Tanenbaum, Goodman: Computerarchitektur, Pearson Studium (Prentice Hall) |
| Pacheco: Parallel Programming with MPI |
| Eijkhout: Introduction to High Performance Computing |
Final exam
| Details |
The students should demonstrate the following competencies in a written exam: The students should demonstrate the following skills in a written exam: 1.) Confident handling of basic terms, mechanisms and concepts. 2.) Parallel programming using common design tools (e.g. MPI and CUDA). 3.) Development of problem solutions that are predestined for the use of parallel computer systems. |
|---|---|
| Minimum standard | At least 50% of the total number of points |
| Exam Type | EN Klausur |
Learning goals
| Goal type | Description |
|---|---|
| Knowledge | basics of parallel programming introduction approach/basic idea Data dependencies and synchronization Parallel computer architectures classification MMID SIMD |
| Knowledge | design of parallel programs development process decomposition pattern completely parallel task parallelism (incl. task pool) divide and conquer pipeline (or general task graph) data parallel (geometric data) recursive data |
| Knowledge | design of parallel programs design pattern for parallel programming master slave (master worker) fork and join single program multiple data (SPMD) multiple program multiple data (MPMD) map reduce loop parallelism mapping of program structure patterns to decomposition patterns |
| Knowledge | design of parallel programs performance Metrics speedup amdahl's law efficiency scalability loss of performance load balancing performance measurement |
| Knowledge | classification of standard libraries with regard to the preceding design options and their use based on design patterns MPI (distributed memory) CUDA (GPU programming) |
| Knowledge | computer architectures (according to Von-Neumann) conceptual components to increase performance regarding ... storage processing units GPU (see above) communication protection |
| Knowledge | implementation of the above concepts in concrete computer architectures IA32e (AMD64) ARM |
| Knowledge | alternative architectures in addition to von-neuman connection of FPGAs to von veumann architectures veural networks implemented in FPGAs |
| Skills | The students are able to - discuss the structure, organization and operating principle of computer systems, - analyze the connection between hardware concepts and the effects on the software, to be able to create efficient programs, - to understand and apply the basic principles of design from the understanding of the interactions of technology, computer concepts and applications, - evaluate and compare computer concepts. |
| Skills | The students are able to - describe architectural features of parallel computers, - evaluate parallel computers, programming paradigms and design patterns and select them for a specific application, - to program parallel computers |
| Skills | specifying system behavior (derived from text documents) |
Expenditure classroom teaching
| Type | Attendance (h/Wk.) |
|---|---|
| Lecture | 2 |
| Exercises (whole course) | 1 |
| Exercises (shared course) | 1 |
| Tutorial (voluntary) | 0 |
Special requirements
|
none |
| Accompanying material | lecture slides (electronic), set of exercises (electronic), tool chains (compile, link, debug, simulate), set of example program codes |
|---|---|
| Separate exam | No |
Learning goals
| Goal type | Description |
|---|---|
| Skills | refer to "Vorlesung/Übung->Lernziele->Fertigkeiten" |
| Skills | targeted use of the software development environment |
| Skills | manage complex tasks as a small team |
| Skills | Development of more complex solutions to problems in the field of compute/data intensive algorithm, signal processing or artificial intelligence or graphic animation that are specific for the use of parallel computers. |
Expenditure classroom teaching
| Type | Attendance (h/Wk.) |
|---|---|
| Practical training | 1 |
| Tutorial (voluntary) | 0 |
Special requirements
|
none |
| Accompanying material | problem and task description (electronic), tool chaine (compile, link, debug, simulate), set of example-codes, self-study tutorials for the tool chain |
|---|---|
| Separate exam | No |
Bei Fehlern, bitte Mitteilung an die
Webredaktion der Fakultät IME
Webredaktion der Fakultät IME
© 2022 Technische Hochschule Köln