GPU-accelerated Image Reduction Pipeline

TL;DR

This paper presents a GPU-accelerated image reduction pipeline that significantly speeds up processing for astronomical observations, enabling faster detection of transient events like gravitational-wave counterparts.

Contribution

The authors developed a novel GPU-based image reduction pipeline using CuPy, achieving over forty times faster processing while preserving existing functionalities.

Findings

Processing speed increased by over 40 times

Maintained all original image reduction functions

Enabled faster detection of astronomical transient events

Abstract

We developed a high-speed image reduction pipeline using Graphics Processing Units (GPUs) as hardware accelerators. Astronomers desire detecting EM counterpart of gravitational-wave sources as soon as possible for sharing positional information to organize systematic follow-up observations. Therefore, high-speed image processing is important. We developed a new image reduction pipeline for our robotic telescope system, which uses a GPU via a Python package CuPy to achieve high-speed image processing. As a result, the processing speed was increased by more than a factor of forty to that of the current pipeline, while maintaining the same functions.