Floating-floating point: a highly accurate number representation with flexible Counting ranges

Itamar Cohen; Gil Einziger

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arXiv · 2410.03692

Floating-floating point: a highly accurate number representation with flexible Counting ranges

Itamar Cohen·Gil Einziger

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Abstract

Efficient number representation is essential for federated learning, natural language processing, and network measurement solutions. Due to timing, area, and power constraints, such applications use narrow bit-width (e.g., 8-bit) number systems. The widely used floating-point systems exhibit a trade-off between the counting range and accuracy. This paper introduces Floating-Floating-Point (F2P) - a floating point number that varies the partition between mantissa and exponent. Such flexibility leads to a large counting range combined with improved accuracy over a selected sub-range. Our evaluation demonstrates that moving to F2P from the state-of-the-art improves network measurement accuracy and federated learning.

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BibTeX RIS

Itamar Cohen, Gil Einziger. 2024-09-22. Floating-floating point: a highly accurate number representation with flexible Counting ranges. https://arxiv.org/abs/2410.03692

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