Astrophysical Supercomputing with GPUs: Critical Decisions for Early Adopters

TL;DR

This paper discusses the critical decisions and strategies for early adoption of GPU computing in astronomy, emphasizing open standards, programming approaches, and the need for training and best practices.

Contribution

It provides a framework for early adopters of GPGPU in astronomy, highlighting key decision areas and advocating for open standards and improved programming practices.

Findings

OpenCL reduces vendor lock-in risks.

Brute force GPU programming is effective.

Early adopters can gain significant benefits.

Abstract

General purpose computing on graphics processing units (GPGPU) is dramatically changing the landscape of high performance computing in astronomy. In this paper, we identify and investigate several key decision areas, with a goal of simplyfing the early adoption of GPGPU in astronomy. We consider the merits of OpenCL as an open standard in order to reduce risks associated with coding in a native, vendor-specific programming environment, and present a GPU programming philosophy based on using brute force solutions. We assert that effective use of new GPU-based supercomputing facilities will require a change in approach from astronomers. This will likely include improved programming training, an increased need for software development best-practice through the use of profiling and related optimisation tools, and a greater reliance on third-party code libraries. As with any new technology, those willing to take the risks, and make the investment of time and effort to become early adopters of GPGPU in astronomy, stand to reap great benefits.