Floating-floating point: a highly accurate number representation with flexible Counting ranges
<|reference_start|>Floating-floating point: a highly accurate number representation with flexible Counting ranges: 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.<|reference_end|>
@article{cohen2024floating-floating,
    title={Floating-floating point: a highly accurate number representation with
  flexible Counting ranges},
    author={Itamar Cohen, Gil Einziger},
    journal={arXiv preprint arXiv:2410.03692},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.03692},
    primaryClass={cs.NI cs.LG}
}