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Next Generation Arithmetic [electronic resource] : Third International Conference, CoNGA 2022, Singapore, March 1–3, 2022, Revised Selected Papers /

Contributor(s): Material type: TextTextSeries: Lecture Notes in Computer Science ; 13253Publisher: Cham : Springer International Publishing : Imprint: Springer, 2022Edition: 1st ed. 2022Description: VII, 135 p. 47 illus., 34 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031097799
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 004.01513 23
LOC classification:
  • QA76.9.C62
Online resources:
Contents:
On the Implementation of Edge Detection Algorithms with SORN Arithmetic -- A Posit8 Decompression Operator for Deep Neural Network Inference -- Qtorch+: Next Generation Arithmetic for Pytorch Machine Learning -- ACTION: Automated Hardware-Software Codesign Framework for Low-precision Numerical Format SelecTION in TinyML -- MultiPosits: Universal Coding of Rn -- Comparing Different Decodings for Posit Arithmetic -- Universal⋆: Reliable, Reproducible, and Energy-Efficient Numerics -- Small reals representations for Deep Learning at the edge: a comparison.
In: Springer Nature eBookSummary: This book constitutes the refereed proceedings of the Third International Conference on Next Generation Arithmetic, CoNGA 2022, which was held in Singapore, during March 1–3, 2022. The 8 full papers included in this book were carefully reviewed and selected from 12 submissions. They deal with emerging technologies for computer arithmetic focusing on the demands of both AI and high-performance computing. .
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On the Implementation of Edge Detection Algorithms with SORN Arithmetic -- A Posit8 Decompression Operator for Deep Neural Network Inference -- Qtorch+: Next Generation Arithmetic for Pytorch Machine Learning -- ACTION: Automated Hardware-Software Codesign Framework for Low-precision Numerical Format SelecTION in TinyML -- MultiPosits: Universal Coding of Rn -- Comparing Different Decodings for Posit Arithmetic -- Universal⋆: Reliable, Reproducible, and Energy-Efficient Numerics -- Small reals representations for Deep Learning at the edge: a comparison.

This book constitutes the refereed proceedings of the Third International Conference on Next Generation Arithmetic, CoNGA 2022, which was held in Singapore, during March 1–3, 2022. The 8 full papers included in this book were carefully reviewed and selected from 12 submissions. They deal with emerging technologies for computer arithmetic focusing on the demands of both AI and high-performance computing. .

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