(2026-08) DYNAFIX; Dynamic Fixed‑Point Encoding for Arbitrary‑Range MPC
2026-08-05
Privacy-preserving computation over real numbers typically employs either floating-point or fixed-point arithmetic. While fixed-point methods are highly efficient, they struggle to handle wide dynamic ranges. Conversely, floating-point methods support a much larger numerical scope but incur overheads more than a hundred times higher than their fixed-point counterparts. In this paper, we propose DYNAFIX, a dynamic fixed-point computation scheme that strikes a balance between floating-point and fixed-point arithmetic. Compared to traditional fixed-point approaches, our scheme supports an arbitrary numerical range; compared to floating-point computation, it maintains performance comparable to fixed-point execution. Experimental results demonstrate that our method achieves a speedup over the state-of-the-art when evaluating high-precision functions, such as the exponential function.