PMID- 32707801
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20200825
IS  - 1424-8220 (Electronic)
IS  - 1424-8220 (Linking)
VI  - 20
IP  - 15
DP  - 2020 Jul 22
TI  - Accelerating Faceting Wide-Field Imaging Algorithm with FPGA for SKA Radio 
      Telescope as a Vast Sensor Array.
LID - 10.3390/s20154070 [doi]
LID - 4070
AB  - 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 20x 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.
FAU - Song, Yuefeng
AU  - Song Y
AUID- ORCID: 0000-0001-7383-0812
AD  - School of Microelectronics, Shanghai Jiao Tong University, Shanghai 200240, 
      China.
FAU - Zhu, Yongxin
AU  - Zhu Y
AD  - School of Microelectronics, Shanghai Jiao Tong University, Shanghai 200240, 
      China.
AD  - Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 
      201210, China.
AD  - University of Chinese Academy of Sciences, Beijing 100049, China.
FAU - Nan, Tianhao
AU  - Nan T
AD  - School of Microelectronics, Shanghai Jiao Tong University, Shanghai 200240, 
      China.
FAU - Hou, Junjie
AU  - Hou J
AD  - School of Microelectronics, Shanghai Jiao Tong University, Shanghai 200240, 
      China.
FAU - Du, Sen
AU  - Du S
AD  - School of Microelectronics, Shanghai Jiao Tong University, Shanghai 200240, 
      China.
FAU - Song, Shijin
AU  - Song S
AD  - School of Microelectronics, Shanghai Jiao Tong University, Shanghai 200240, 
      China.
LA  - eng
GR  - U1831118/the National Natural Science Foundation of China/
PT  - Journal Article
DEP - 20200722
PL  - Switzerland
TA  - Sensors (Basel)
JT  - Sensors (Basel, Switzerland)
JID - 101204366
SB  - IM
PMC - PMC7436031
OTO - NOTNLM
OT  - FPGA
OT  - SKA
OT  - big data technologies
OT  - cloud computing
OT  - gridding
OT  - phase rotation
COIS- The authors declare no conflict of interest.
EDAT- 2020/07/28 06:00
MHDA- 2020/07/28 06:01
PMCR- 2020/08/01
CRDT- 2020/07/26 06:00
PHST- 2020/04/05 00:00 [received]
PHST- 2020/07/08 00:00 [revised]
PHST- 2020/07/14 00:00 [accepted]
PHST- 2020/07/26 06:00 [entrez]
PHST- 2020/07/28 06:00 [pubmed]
PHST- 2020/07/28 06:01 [medline]
PHST- 2020/08/01 00:00 [pmc-release]
AID - s20154070 [pii]
AID - sensors-20-04070 [pii]
AID - 10.3390/s20154070 [doi]
PST - epublish
SO  - Sensors (Basel). 2020 Jul 22;20(15):4070. doi: 10.3390/s20154070.