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Next Generation Arithmetic for Edge Computing

Authors :
Martin Langhammer
Rainer Leupers
Andre Guntoro
Florent de Dinechin
John L. Gustafson
Farhad Merchant
Cecilia De la Parra
Sangeeth Nambiar
Robert Bosch Gmbh [Schwieberdingen]
Rheinisch-Westfälische Technische Hochschule Aachen University (RWTH)
Software and Cognitive radio for telecommunications (SOCRATE)
Inria Grenoble - Rhône-Alpes
Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-CITI Centre of Innovation in Telecommunications and Integration of services (CITI)
Institut National des Sciences Appliquées de Lyon (INSA Lyon)
Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National des Sciences Appliquées de Lyon (INSA Lyon)
Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)
National University of Singapore (NUS)
Intel Corporation [Salisbury]
Bosch Research and Technology Center [Bangalore]
Rheinisch-Westfälische Technische Hochschule Aachen (RWTH)
Source :
DATE 2020-Design, Automation and Test in Europe Conference, DATE 2020-Design, Automation and Test in Europe Conference, Mar 2020, Grenoble, France. pp.1357-1365, ⟨10.23919/DATE48585.2020.9116196⟩, DATE
Publication Year :
2020
Publisher :
HAL CCSD, 2020.

Abstract

International audience; Arithmetic is a key component and is ubiquitous in today's digital world, ranging from embedded to high-performance computing systems. With machine learning at the fore in a wide range of application domains from wearables to automotive to avionics to weather prediction, sufficiently accurate yet low-cost arithmetic is the need for the day. Recently, there have been several advances in the domain of computer arithmetic, which includes high-precision anchored numbers from ARM, posit arithmetic, bfloat16, etc. as an alternative to IEEE 754-2008 compliant arithmetic. Optimizations on fixed-point and integer arithmetic are also being pursued actively for low-power computing architectures. Furthermore, approximate computing and transprecision/mixed-precision computing have been exciting areas of research forever. While academic research in the domain of computer arithmetic has a long history, industrial adoption of some of these new data types and techniques is in its early stages and expected to increase in the future. bfloat16 is an excellent example for this. In this paper, we bring academia and industry together to discuss the latest results and future directions for research in the domain of next-generation computer arithmetic, especially for edge computing.

Details

Language :
English
Database :
OpenAIRE
Journal :
DATE 2020-Design, Automation and Test in Europe Conference, DATE 2020-Design, Automation and Test in Europe Conference, Mar 2020, Grenoble, France. pp.1357-1365, ⟨10.23919/DATE48585.2020.9116196⟩, DATE
Accession number :
edsair.doi.dedup.....41a2f3492563b2e945c88e3dddaaca2e