Publication detail

Editorial: Special issue on Advancing on Approximate Computing: Methodologies, Architectures and Algorithms

BARBARESCHI, M. BOSIO, A. SEKANINA, L. BRAUN, C.

Original Title

Editorial: Special issue on Advancing on Approximate Computing: Methodologies, Architectures and Algorithms

Type

editorial

Language

English

Original Abstract

In the modern computing era, characterized by saturated performance and high production costs, Approximate Computing has been representing the most attractive breakthrough for efficient system design. Such an innovative paradigm leverages the intrinsic error resilience of applications to inaccuracy in their inner calculations, in order to trade output result quality, under a certain maximum acceptable error threshold, off for system performance gain, such as calculation time and power demanding. In particular, for audio, image and video processing, data mining and information retrieval, approximate results turn out hard to distinguish from perfect ones, while their computation is less expensive. In recent years, Approximate Computing applicability is broadening in many scientific areas since suitable solutions come from approximate arithmetic operators, implemented both at hardware and software level, but from unreliable memory architectures, integrated circuit test, compilers and many others too. This special issue is dedicated to original research results and achievements by researcher community working on challenges and issues related to Approximate Computing

Keywords

approximate circuit, approximate computing, error modeling and propagation, inherent error resiliency

Authors

BARBARESCHI, M.; BOSIO, A.; SEKANINA, L.; BRAUN, C.

Released

30. 6. 2021

ISBN

0167-739X

Periodical

Future Generation Computer Systems-The International Journal of Grid Computing Theory Methods and Applications

Year of study

124

Number

1

State

Kingdom of the Netherlands

Pages from

54

Pages to

55

Pages count

2

BibTex

@misc{BUT175800,
  author="BARBARESCHI, M. and BOSIO, A. and SEKANINA, L. and BRAUN, C.",
  title="Editorial: Special issue on Advancing on Approximate Computing: Methodologies, Architectures and Algorithms",
  year="2021",
  journal="Future Generation Computer Systems-The International Journal of Grid Computing Theory Methods and Applications",
  volume="124",
  number="1",
  pages="54--55",
  doi="10.1016/j.future.2021.05.027",
  issn="0167-739X",
  note="editorial"
}