Accelerating radio astronomy cross-correlation with graphics processing units. (May 2013)

• Record Type: Journal Article
• Authors: Clark, M.A.; Plante, PC La; Greenhill, L.J.
• Is Part Of: International journal of high performance computing applications. Volume 27:Number 2(2013)
• Page Start: 178
• Page End: 192
• Publication Date: 2013-05
• Subjects: radio astronomy -- graphics processing units -- signal processing -- correlation; High performance computing -- Periodicals; Supercomputers -- Periodicals; 004.1105
• DOI: 10.1177/1094342012444794
• Languages: English
• ISSNs: 1094-3420

Abstract

We present a highly parallel implementation of the cross-correlation of time-series data using graphics processing units (GPUs), which is scalable to hundreds of independent inputs and suitable for the processing of signals from 'large-N ' arrays of many radio antennas. The computational part of the algorithm, the X-engine, is implemented efficiently on NVIDIA's Fermi architecture, sustaining up to 79% of the peak single-precision floating-point throughput. We compare performance obtained for hardware- and software-managed caches, observing significantly better performance for the latter. The high performance reported involves use of a multi-level data tiling strategy in memory and use of a pipelined algorithm with simultaneous computation and transfer of data from host to device memory. The speed of code development, flexibility, and low cost of the GPU implementations compared with application-specific integrated circuit (ASIC) and field programmable gate array (FPGA) implementations have the potential to greatly shorten the cycle of correlator development and deployment, for cases where some power-consumption penalty can be tolerated.