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DT8117

Heterogenous & Cloud Computing

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This course is no longer taught and is only available for examination.

Credits 7.5
Level Doctoral degree level
Course start Spring
Duration 1 semester
Language of instruction English
Location Trondheim

About

About the course

Course content

The goal is to study the use of heterogeneous systems for intense computational tasks and well as cloud technologies that facilitate these. Focus will be on numerical problems, including combining numerical simulations with graphics processing of large volumes of data and/or applications with real-time requirements. The content of the course will be adapted to the students interests and background.

Learning outcome

The main goal of this course is to give the participants insights into newer technologies within grid and heterogeneous computing systems, including techniques for optimizing algorithms for many-core technologies. Knowledge: The candidate will gain insights to the plethora of abstraction levels associated with current and future developments within heterogeneous computing -- from maintaining programmability on single systems with several layers of caches, to the technologies behind Grid and Cloud computing. Skills: The problemsets/miniprojects will give experience with experimental methods of analyzing heterogeneous computing resources related to the candidates own research topic, as well as how to systematically do a literature review in this context. Compentence: Ability to handle newer technologies withing grid and heterogeneous systems, including techniques for optimizing algorithms on many-core systems.

Learning methods and activities

Graduate seminar serie where graduate students activly participate, as well as 2 projects which may include implementations and analysis of related topics.

Further on evaluation

In the event of voluntary repetition, fail ("Not passed'") or valid absence, all course-activities must be retaken in a semester with teaching.

Required previous knowledge

TDT 4200 Parallel Computing or waiver from instructor

Course materials

Chosen based on need.

Subject areas

  • Computer Systems

Contact information

Course coordinator

Department with academic responsibility

Department of Computer Science