High performance power spectrum analysis using a FPGA based reconfigurable computing platform

被引:0
|
作者
Abhyankar, Yogindra [1 ]
C, Sajish [1 ]
Agarwal, Yogesh [1 ]
Subrahmanya, C. R. [2 ]
Prasad, Peeyush [2 ]
机构
[1] Ctr Dev Adv Comp, Hardware Technol Dev Grp, Pune 411007, Maharashtra, India
[2] Raman Res Inst, Dept Astron & Astrophys, Bangalore 560 080, Karnataka, India
关键词
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Power-spectrum analysis is an important tool providing critical information about a signal. The range of applications includes communication-systems to DNA-sequencing. If there is interference present on a transmitted signal, it could be due to a natural cause or superimposed forcefully. In the later case, its early detection and analysis becomes important. In such situations having a small observation window, a quick look at power-spectrum can revel a great deal of information, including frequency and source of interference. In this paper, we present our design of a FPGA based reconfigurable platform for high performance power-spectrum analysis. This allows for the real-time data-acquisition and processing of samples of the incoming signal in a small time frame. The processing consists of computation of power, its average and peak, over a set of input values. This platform sustains simultaneous data streams on each of the four input channels.
引用
收藏
页码:328 / +
页数:2
相关论文
共 50 条
  • [31] High-performance reconfigurable computing
    Buell, Duncan
    El-Ghazawi, Tarek
    Gaj, Kris
    Kindratenko, Volodymyr
    COMPUTER, 2007, 40 (03) : 23 - 27
  • [32] Accelerating FCM Algorithm Using High-Speed FPGA Reconfigurable Computing Architecture
    Almomany, Abedalmuhdi
    Jarrah, Amin
    Al Assaf, Anwar
    JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, 2023, 18 (04) : 3209 - 3217
  • [33] Accelerating FCM Algorithm Using High-Speed FPGA Reconfigurable Computing Architecture
    Abedalmuhdi Almomany
    Amin Jarrah
    Anwar Al Assaf
    Journal of Electrical Engineering & Technology, 2023, 18 : 3209 - 3217
  • [34] An Open Reconfigurable Research Platform as Stepping Stone to Exascale High-Performance Computing
    Stroobandt, Dirk
    Ciobanu, Catalin Bogdan
    Santambrogio, Marco D.
    Figueiredo, Gabriel
    Brokalakis, Andreas
    Pnevmatikatos, Dionisios
    Huebner, Michael
    Becker, Tobias
    Thom, Alex J. W.
    PROCEEDINGS OF THE 2017 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE), 2017, : 416 - 421
  • [35] Design Optimization for High-Performance Computing Using FPGA
    Isik, Murat
    Inadagbo, Kayode
    Aktas, Hakan
    INFORMATION MANAGEMENT AND BIG DATA, SIMBIG 2023, 2024, 2142 : 142 - 156
  • [36] Reconfigurable computing for high performance computing computational science
    Park, Song Jun
    Henz, Brian
    Shires, Dale
    PROCEEDINGS OF THE HPCMP USERS GROUP CONFERENCE 2007, 2007, : 350 - 358
  • [37] Performance analysis of linear algebraic functions using reconfigurable computing
    Damaj, I
    Diab, H
    JOURNAL OF SUPERCOMPUTING, 2003, 24 (01): : 91 - 107
  • [38] Performance Analysis of Linear Algebraic Functions Using Reconfigurable Computing
    Issam Damaj
    Hassan Diab
    The Journal of Supercomputing, 2003, 24 : 91 - 107
  • [39] FPGA based hardware architectures for high performance computing applications
    Belean, Bogdan
    Pogacian, Sergiu
    Bot, Adrian
    2012 5TH ROMANIA TIER 2 FEDERATION GRID, CLOUD & HIGH PERFORMANCE COMPUTING SCIENCE (RO-LCG), 2012, : 11 - 14
  • [40] Power analysis security evaluation on Piccolo based on FPGA platform
    Wang, Chen-Xu
    Li, Jing-Hu
    Yu, Ming-Yan
    Wang, Jin-Xiang
    Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology, 2014, 36 (01): : 101 - 107