A fast-turnaround pipeline for realtime data reduction plays an essential
role in discovering and permitting follow-up observations to young supernovae
and fast-evolving transients in modern time-domain surveys. In this paper, we
present the realtime image subtraction pipeline in the intermediate Palomar
Transient Factory. By using high-performance computing, efficient database, and
machine learning algorithms, this pipeline manages to reliably deliver
transient candidates within ten minutes of images being taken. Our experience
in using high performance computing resources to process big data in astronomy
serves as a trailblazer to dealing with data from large-scale time-domain
facilities in near future.Comment: 18 pages, 6 figures, accepted for publication in PAS