A performance enhancement of the Payne-Hanek range reduction algorithm

Abstract

Range reduction plays a crucial role in the accuracy and performance of evaluating trigonometric functions, and is often the primary bottleneck for large floating-point inputs. While fast algorithms such as Cody--Waite work efficiently over narrow intervals, the Payne--Hanek algorithm remains the standard technique for accurate reduction across large floating-point inputs. However, many existing implementations of Payne--Hanek suffer from high latency due to heavy branching, conversion overheads, and the use of multi-word integer arithmetic, which hinders SIMD vectorization. In this paper, we analyze and present a branch-free variation of the Payne--Hanek algorithm using only floating-point arithmetic. Our method operates directly over large double-precision inputs ($|x|\ge 2^{16}$) and is well suited to hardware with FMA instructions. We formulate the precision constraints in terms of a truncation error budget, construct a compact lookup table indexed by the input exponent, and prove that the scaled reduced argument has absolute error below $2^{-110}$ and relative error below $2^{-60}$ for every input, including worst cases. The same routine can serve both as the complete range reduction of a single-stage implementation and as the fast path of a correctly rounded one, achieving higher throughput than existing implementations and lower latency than those returning a double-double reduced argument. The algorithm is currently implemented in the LLVM libc project.

Updated to include CORE-MATH newer Payne-Hanek range reduction implementation, and add CRLIBM to performance analysis. Updated the performance table after fixing the setup