2 papers
cs.AR2026
FlexPosit: Tunable Fractional Precision for LLM Inference Accelerators
Yimin Gao, Liangtao Dai, Jun Yin +2
Large language models (LLMs) offer remarkable capabilities but impose prohibitive compute and energy costs. Quantization governs the trade-offs between accuracy and hardware effici…
math.NA2023
A Numerical-based Parametric Error Analysis Method for Goldschmidt Floating Point Division
Binzhe Yuan, Liangtao Dai, Xin Lou
This paper proposes a parametric error analysis method for Goldschmidt floating point division, which reveals how the errors of the intermediate results accumulate and propagate du…