On the Efficacy and High-Performance Implementation of Quaternion Matrix Multiplication
pith:P2553T6C Add to your LaTeX paper
What is a Pith Number?\usepackage{pith}
\pithnumber{P2553T6C}
Prints a linked pith:P2553T6C badge after your title and writes the identifier into PDF metadata. Compiles on arXiv with no extra files. Learn more
read the original abstract
Quaternion symmetry is ubiquitous in the physical sciences. As such, much work has been afforded over the years to the development of efficient schemes to exploit this symmetry using real and complex linear algebra. Recent years have also seen many advances in the formal theoretical development of explicitly quaternion linear algebra with promising applications in image processing and machine learning. Despite these advances, there do not currently exist optimized software implementations of quaternion linear algebra. The leverage of optimized linear algebra software is crucial in the achievement of high levels of performance on modern computing architectures, and thus provides a central tool in the development of high-performance scientific software. In this work, a case will be made for the efficacy of high-performance quaternion linear algebra software for appropriate problems. In this pursuit, an optimized software implementation of quaternion matrix multiplication will be presented and will be shown to outperform a vendor tuned implementation for the analogous complex matrix operation. The results of this work pave the path for further development of high-performance quaternion linear algebra software which will improve the performance of the next generation of applicable scientific applications.
This paper has not been read by Pith yet.
Forward citations
Cited by 1 Pith paper
-
Representations of 3D Rotations: Mathematical Foundations and Comparative Analysis
A comparative review of SO(3) rotation representations finds quaternions dominant for compactness and efficiency while 6D continuous and probabilistic methods improve continuity and uncertainty handling.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.