FPGA Implementation of the Multiplication Operation in Multiple-Precision Arithmetic

被引:0
作者
Rudnicki, Kamil [1 ]
Stefanski, Tomasz P. [2 ]
机构
[1] Brightelligence Inc, Dept Reconfigurable Syst, Glasgow, Lanark, Scotland
[2] Gdansk Univ Technol, Fac Elect Telecommun & Informat, PL-80233 Gdansk, Poland
来源
PROCEEDINGS OF THE 24TH INTERNATIONAL CONFERENCE MIXED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS - MIXDES 2017 | 2017年
关键词
FPGAs; multiple-precision arithmetic; scientific computing; parallel processing; embedded systems; COMPUTATION;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Although standard 32/64-bit arithmetic is sufficient to solve most of the scientific-computing problems, there are still problems that require higher numerical precision. Multiple-precision arithmetic (MPA) libraries are software tools for emulation of computations in a user-defined precision. However, availability of a reconfigurable cards based on field-programmable gate arrays (FPGAs) in computing systems allows one to implement MPA algorithms in hardware. Whereas addition and subtraction operations of two n-digit numbers require O(n) operations, the basecase multiplication is equivalent to the convolution computation that requires O(n 2) operations. Therefore, an efficient implementation of the multiplication operation is crucial for application of the reconfigurable hardware in MPA computations. In this contribution, our implementation of the basecase-multiplication algorithm in MPA on FPGA is presented. The method is implemented using the very high speed integrated circuit hardware description language (VHDL) and benchmarked on Xilinx Artix-7 FPGA. In the developed implementation of the MPA multiplication, the multiplication of two integer 1024-bit numbers (2048-bit numbers) takes 205 nsec (819 nsec) with the use of 40 DSP modules. It gives two-fold speedup in comparison to the reference results published in the literature. The developed digital circuit of the MPA multiplier works with integer numbers of precision varying in the range between 16 bits and 32 kbits. Such a scalability allows one to use the developed method not only in scientific computing, but also in embedded systems employing encryption based on MPA.
引用
收藏
页码:271 / 275
页数:5
相关论文
共 12 条
  • [1] [Anonymous], 2016, GNU multiple precision arithmetic library 6. 1. 2
  • [2] High-precision computation: Mathematical physics and dynamics
    Bailey, D. H.
    Barrio, R.
    Borwein, J. M.
    [J]. APPLIED MATHEMATICS AND COMPUTATION, 2012, 218 (20) : 10106 - 10121
  • [3] High-precision floating-point arithmetic in scientific computation
    Bailey, DH
    [J]. COMPUTING IN SCIENCE & ENGINEERING, 2005, 7 (03) : 54 - 61
  • [4] Daemen J., 2002, DESIGN RIJNDAEL AES, DOI DOI 10.1007/978-3-662-04722-4
  • [5] IBM, 2009, SYST Z9 ENT CLASS SY
  • [6] Kalathungal A., 2013, THESIS
  • [7] KARABUTSA A, 1962, DOKL AKAD NAUK SSSR+, V145, P293
  • [8] Knuth D. E., ART COMPUTER PROGRAM, V2
  • [9] Lei Y., 2011, LECT NOTES COMPUTER, V6965
  • [10] RIVEST RL, 1978, COMMUN ACM, V21, P120, DOI [10.1145/359340.359342, 10.1145/357980.358017]