Image-Domain Gridding on Graphics Processors

Veenboer, Bram; Petschow, Matthias; Romein, John W.

doi:10.1109/ipdps.2017.68

Cited by 18 publications

(23 citation statements)

References 20 publications

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“…We plan to improve the analysis in the future by improving the enforcement of spectral smoothness in calibration, better modelling of the instrument (improving beam models) and by using the new Image Domain Gridder (IDG) combined with WSClean (see e.g. Veenboer et al 2017;van der Tol, Sebastiaan et al 2018) to subtract off-axis sources. The upcoming LOFAR 2.0 upgrade will also increase the sensitivity of the LOFAR-LBA system.…”

Section: Discussionmentioning

confidence: 99%

The first power spectrum limit on the 21-cm signal of neutral hydrogen during the Cosmic Dawn at z = 20–25 from LOFAR

Gehlot

Mertens

Koopmans

et al. 2019

Monthly Notices of the Royal Astronomical Society

102

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Observations of the redshifted 21-cm hyperfine line of neutral hydrogen from early phases of the Universe such as Cosmic Dawn and the Epoch of Reionization promise to open a new window onto the early formation of stars and galaxies. We present the first upper limits on the power spectrum of redshifted 21-cm brightness temperature fluctuations in the redshift range z = 19.8 − 25.2 (54 − 68 MHz frequency range) using 14 hours of data obtained with the LOFAR-Low Band Antenna (LBA) array. We also demonstrate the application of a multiple pointing calibration technique to calibrate the LOFAR-LBA dual-pointing observations centred on the North Celestial Pole and the radio galaxy 3C220.3. We observe an unexplained excess of ∼ 30 − 50% in Stokes I noise compared to Stokes V for the two observed fields, which decorrelates on 12 seconds and might have a physical origin. We show that enforcing smoothness of gain errors along frequency direction during calibration reduces the additional variance in Stokes I compared Stokes V introduced by the calibration on sub-band level. After subtraction of smooth foregrounds, we achieve a 2σ upper limit on the 21-cm power spectrum of ∆ 2 21 < (14561 mK) 2 at k ∼ 0.038 h cMpc −1 and ∆ 2 21 < (14886 mK) 2 at k ∼ 0.038 h cMpc −1 for the 3C220 and NCP fields respectively and both upper limits are consistent with each other. The upper limits for the two fields are still dominated by systematics on most k modes.

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Section: Discussionmentioning

confidence: 99%

The first power spectrum limit on the 21-cm signal of neutral hydrogen during the Cosmic Dawn at z = 20–25 from LOFAR

Gehlot

Mertens

Koopmans

et al. 2019

Monthly Notices of the Royal Astronomical Society

102

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“…For these sources, with inverse process (FFT and degridding) the visibilities are ''predicted'' and subtracted from the input to reveal fainter sources. This process is repeated until the sky model converges [12], [13].…”

Section: Background and Related Work A Imaging Phase In Radio Tmentioning

confidence: 99%

“…At present, the widely used gridding/degridding approaches in creating wide-field images include W-projection, W-stacking, A-projection, and AW-projection [12]. W-projection [17] corrects for the W-term through a convolution in Fourier space, and it uses different convolution matrices for different values of w. W-Stacking [18] uses a w-plane dependent grid which is different from the wplane dependent convolution function in W-projection, and the samples are gridded to the grid corresponding to the nearest w-plane.…”

Section: B Related Workmentioning

confidence: 99%

FPGA-Based Scale-Out Prototyping of Degridding Algorithm for Accelerating Square Kilometre Array Telescope Data Processing

Hou

Zhu

et al. 2020

IEEE Access

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The SKA (Square Kilometre Array) radio telescope will become the most sensitive telescope by correlating a large number of antenna nodes to form a giant antenna array. The data generated from such a large number of antenna nodes will pose a huge storage problem and require real-time data processing to make the best use of data, and the SKA Scientific Data Processing becomes the bottleneck of the whole processing flow. However, the existing high-performance CPU-and GPU (Graphics Processing Unit)-based solutions cannot satisfy the performance requirements and power budget requirements well [1]. Due to the consideration of the high energy efficiency of hardware accelerators and the flexibility and cost of prototype design, in this paper, we explore the FPGA(Field Programmable Gate Array)-based prototype of one of the most computationally demanding procedures in SKA scientific data processing: degridding. Through the analysis of algorithm behavior and bottlenecks, we design and optimize the memory architecture and computing logic of an FPGA-based prototype. Besides, with the consideration of the relations between the required data of processing multiple spectral channels, we reuse the shared data in processing neighboring spectral channels, and the performance further improves. The functionality and performance of our design have been verified on the target FPGA board, and the software-based benchmarks were also measured on comparable CPU and GPU platforms, indicating that the FPGA-based prototype achieves 2.74 times and 2.03 times speedup, 7.64 times and 7.42 times energy efficiency than the MPI(Message Passing Interface)-based CPU benchmark and the CUDA (Compute Unified Device Architecture)-based GPU benchmark, respectively. INDEX TERMS FPGA, gridding/degridding, scientific data processing, square kilometre array.

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“…Based on Romein's algorithm, Merry [26] presents a thread coarsening method where the multiple work items are merged into one across parallel work items to improve instruction-level parallelism and the efficiency of gridding computing for single-polarization and quad-polarization on the target GPUs. Veenboer et al [10] initiated the CPUs-based and GPUs-based image-domain gridding (IDG) algorithm and first presented the efficient degridding implementation on GPUs. They presented a parallelization and optimization strategy on gridder kernel and degridder kernel and the result was demonstrated in close to optimal performance on different platforms of CPUs and GPUs.…”

Section: Related Workmentioning

confidence: 99%

“…Unlike optical telescopes, which typically consist of a single receiver, modern radio telescopes such as SKA consist of many small antennas. Three steps are required in general to build a sky image: (1) different correlated pairs of stations generate digital signals, namely visibilities, (2) instrument parameters and environmental effects are estimated by calibration, and (3) the imaging steps partially correct the visibility into the sky image [10].…”

Section: Introductionmentioning

confidence: 99%

Accelerating Faceting Wide-Field Imaging Algorithm with FPGA for SKA Radio Telescope as a Vast Sensor Array

Song

Zhu

Nan

et al. 2020

Sensors

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The SKA (Square Kilometer Array) radio telescope will become the most sensitive telescope by correlating a huge number of antenna nodes to form a vast array of sensors in a region over one hundred kilometers. Faceting, the wide-field imaging algorithm, is a novel approach towards solving image construction from sensing data where earth surface curves cannot be ignored. However, the traditional processor of cloud computing, even if the most sophisticated supercomputer is used, cannot meet the extremely high computation performance requirement. In this paper, we propose the design and implementation of high-efficiency FPGA (Field Programmable Gate Array) -based hardware acceleration of the key algorithm, faceting in SKA by focusing on phase rotation and gridding, which are the most time-consuming phases in the faceting algorithm. Through the analysis of algorithm behavior and bottleneck, we design and optimize the memory architecture and computing logic of the FPGA-based accelerator. The simulation and tests on FPGA are done to confirm the acceleration result of our design and it is shown that the acceleration performance we achieved on phase rotation is 20× the result of the previous work. We then further designed and optimized an efficient microstructure of loop unrolling and pipeline for the gridding accelerator, and the designed system simulation was done to confirm the performance of our structure. The result shows that the acceleration ratio is 5.48 compared to the result tested on software in gridding parts. Hence, our approach enables efficient acceleration of the faceting algorithm on FPGAs with high performance to meet the computational constraints of SKA as a representative vast sensor array.

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Image-Domain Gridding on Graphics Processors

Cited by 18 publications

References 20 publications

The first power spectrum limit on the 21-cm signal of neutral hydrogen during the Cosmic Dawn at z = 20–25 from LOFAR

The first power spectrum limit on the 21-cm signal of neutral hydrogen during the Cosmic Dawn at z = 20–25 from LOFAR

FPGA-Based Scale-Out Prototyping of Degridding Algorithm for Accelerating Square Kilometre Array Telescope Data Processing

Accelerating Faceting Wide-Field Imaging Algorithm with FPGA for SKA Radio Telescope as a Vast Sensor Array

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