Acceleration of multi-component multiple-precision arithmetic with branch-free algorithms and SIMD vectorization

TL;DR

This paper demonstrates how branch-free algorithms combined with SIMD vectorization can significantly speed up multi-component multiple-precision arithmetic on x86 and ARM CPUs, especially for high-precision computations.

Contribution

It introduces and benchmarks branch-free, SIMD-optimized algorithms for multi-component multiple-precision arithmetic on modern CPU architectures.

Findings

Significant acceleration in linear computations and polynomial evaluation.

Effective implementation on both x86 and ARM CPU platforms.

Abstract

Multiple-precision floating-point branch-free algorithms can significantly accelerate multi-component arithmetic implemented by combining hardware-based binary64 and binary32, particularly for triple- and quadruple-precision computations. In this study, we achieved benchmark results on x86 and ARM CPU platforms to quantify the accelerations achieved in linear computations and polynomial evaluation by integrating these algorithms.