From a Lossless (~1.5:1) Compression Algorithm for Llama2 7B Weights to
  Variable Precision, Variable Range, Compressed Numeric Data Types for CNNs
  and LLMs
Vincenzo Liguori
This paper starts with a simple lossless ~1.5:1 compression algorithm for the
weights of the Large Language Model (LLM) Llama2 7B [1] that can be implemented
in ~200 LUTs in AMD FPGAs, processing over 800 million bfloat16 numbers per
second. This framework is then extended to variable precision, variable range,
compressed numerical data types that are a user defined super set of both
floats and posits [2]. The paper then discusses a simple hardware
implementation of such format based on ANS (Asymmetrical Numeral Systems) [3]
that acts as a bridge between this flexible data format and a computational
engine while, at the same time, achieving bandwidth reduction. An example of a
token factory using weight compression and sharing is also given.