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Syllabus for

Academic year
EDA280 - Parallel computer systems
 
Owner: TDATA
4,0 Credits (ECTS 6)
Grading: TH - Five, Four, Three, Not passed
Level: A
Department: 37 - COMPUTER SCIENCE AND ENGINEERING


Teaching language: Swedish

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 No Sp
0193 Examination 4,0 c Grading: TH   2,0 c 2,0 c   26 May 2007 pm V,  27 Aug 2007 pm V

In programs

TDATA COMPUTER SCIENCE AND ENGINEERING - Embedded computer systems engineering, Year 4 (elective)
TITEA SOFTWARE ENGINEERING, Year 4 (elective)
TITEA SOFTWARE ENGINEERING, Year 3 (elective)
DCMAS MSc PROGR IN DEPENDABLE COMPUTER SYSTEMS - Dependable Programming, Year 1 (elective)
DCMAS MSc PROGR IN DEPENDABLE COMPUTER SYSTEMS - Dependable Architectures, Year 1 
TELTA ELECTRICAL ENGINEERING, Year 4 (elective)

Examiner:

Professor  Per Stenström



Eligibility:

For single subject courses within Chalmers programmes the same eligibility requirements apply, as to the programme(s) that the course is part of.

Course specific prerequisites

EDA 111 Computer Architecture

Aim

To provide a fundamental insight into the design principles for general-pupose parallel computer systems.

Goal

After completion of the course, the student will have ained conceptual as well as practical insights into prevailing parallel programming models and techniques for parallel computer systems - multiprocessors and clusters. In addition, the course will provide the student with indepth knowledge about design principles of parallel computer systems. This includes, but is not limited to, semantic models of memory systems for parallel computer systems, design principles of cache coherence and message passing protocols, interconnection networks, performance
metrics and scalability models.

Content

Shared address-space as well as distributed memory (private address-space) machines use commodity high-performance microprocessors but differ in the fundamental programming models offered to the software systems. The course first introduces the two programming models they offer to the software: The shared address-space model and the message-passing model. In laboratory work, the course participants will have a chance to get insights into parallel programming through basic programming assignments. In particular, we will learn about strategies for how algorithms that were originally developed for single-processor systems can be converted to run efficiently on parallel computers using the shared address-space programming model.

The main part of the course is devoted to design principles for parallel computer architectures. Studies will be done on how memory systems for multiprocessor and distributed memory systems are designed. The most critical aspect of this is how to deal with scalability, namely, how to make performance scale for memory systems and interconnection networks in a cost-effective manner. Important concepts that are treated are memory consistency models, cache coherence, interconnection networks, and latency tolerating techniques to mention a few.

Organisation

The course is partly a self study course where the text book defines the content. To make it easier to go through and comprehend the material, the course contains lectures, exercises and laborations. The content of the course follows closely the text book and each lecture introduces and summarizes one subject area from the text book. In total, there are 12 lectures and exercises, and 2 laborations.

Literature

Culler, Singh, Gupta. Parallel Computer Architecture: A Hardware/Software Approach. Morgan Kaufmann Publishers Inc. San Francisco, 1998.

Examination

Written exam and pass on Laboratory.


Page manager Published: Thu 03 Nov 2022.