FPGA-based Acceleration of FT Convolution for Pulsar Search Using OpenCL
Department of Electrical and Computer Engineering, University of Auckland, Private Bag 92019, Auckland 1142, New Zealand
arXiv:1805.12280 [cs.DC], (31 May 2018)
@article{wang2018fpgabased,
title={FPGA-based Acceleration of FT Convolution for Pulsar Search Using OpenCL},
author={Wang, Haomiao and Thiagaraj, Prabu and Sinnen, Oliver},
year={2018},
month={may},
archivePrefix={"arXiv"},
primaryClass={cs.DC}
}
The Square Kilometre Array (SKA) project will be the world largest radio telescope array. With its large number of antennas, the number of signals that need to be processed is dramatic. One important element of the SKA’s Central Signal Processor package is pulsar search. This paper focuses on the FPGA-based acceleration of the Frequency-Domain Acceleration Search module, which is a part of SKA pulsar search engine. In this module, the frequency-domain input signals have to be processed by 85 Finite Impulse response (FIR) filters within a short period of limitation and for thousands of input arrays. Because of the large scale of the input length and FIR filter size, even high-end FPGA devices cannot parallelise the task completely. We start by investigating both time-domain FIR filter (TDFIR) and frequency-domain FIR filter (FDFIR) to tackle this task. We applied the overlap-add algorithm to split the coefficient array of TDFIR and the overlap-save algorithm to split the input signals of FDFIR. To achieve fast prototyping design, we employed OpenCL, which is a high-level FPGA development technique. The performance and power consumption are evaluated using multiple FPGA devices simultaneously and compared with GPU results, which is achieved by porting FPGA-based OpenCL kernels. The experimental evaluation shows that the FDFIR solution is very competitive in terms of performance, with a clear energy consumption advantage over the GPU solution.
June 2, 2018 by hgpu
