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Approximate Computing

Approximate Computing
type: Seminar (S) links:
semester: WS 17/18
lecturer: Tanfer Alan
Jorge Castro-Godínez
Prof. Dr.-Ing. Jörg Henkel
SWS: 2
lv-no.: 2424010

Approximate Computing is a modern design paradigm that aims to exploit the inherent tolerance to errors in a wide set of applications. Providing good enough results in applications such as image processing and financial analy-sis, where a unique or golden answer does not exist, this paradigm improve performance in terms of execution time, area, and power/energy, even by or-ders of magnitude. This can be achieved, for instance, by skipping non-critical computations at software level, or reducing circuit complexity and lowering the operation voltage at hardware level.


In this seminar we are interested in studying the applicability of Approximate Computing in all the abstraction layers, from opera-tive systems and applica-tions to architecture and arithmetic components, keeping a particular interest in the cross-layer interaction of approximations and the development of metho-dologies and tools to implement Approximate Computing.