A hybrid architecture for astronomical computing

TL;DR

This paper proposes a hybrid computing architecture tailored for astronomical big data processing, integrating HPC and big data technologies to optimize resource management and support large-scale astronomical data analysis.

Contribution

It introduces a novel hybrid architecture infrastructure that combines HPC and big data processing, optimized for astronomical applications based on the China-VO Astronomy Cloud project.

Findings

Optimized hardware architecture for hybrid computing.

Enhanced cluster management and resource scheduling.

Improved support for astronomical big data processing.

Abstract

With many large science equipment constructing and putting into use, astronomy has stepped into the big data era. The new method and infrastructure of big data processing has become a new requirement of many astronomers. Cloud computing, Map/Reduce, Hadoop, Spark, etc. many new technology has sprung up in recent years. Comparing to the high performance computing(HPC), Data is the center of these new technology. So, a new computing architecture infrastructure is necessary, which can be shared by both HPC and big data processing. Based on Astronomy Cloud project of Chinese Virtual Observatory (China-VO), we have made much efforts to optimize the designation of the hybrid computing platform. which include the hardware architecture, cluster management, Job and Resource scheduling.