FPGA-orthopoly: a hardware implementation of orthogonal polynomials

被引:0
|
作者
Asghari, M. [1 ]
Rasanan, A. H. Hadian [1 ,2 ]
Gorgin, S. [3 ,4 ]
Rahmati, D. [5 ]
Parand, K. [2 ,6 ,7 ]
机构
[1] Inst Res Fundamental Sci, Sch Comp Sci, Farmanieh Campus, Tehran, Iran
[2] Shahid Beheshti Univ, Inst Cognit & Brain Sci, GC, Tehran, Iran
[3] Iranian Res Org Sci & Technol IROST, Dept Elect Engn & Informat Technol, Tehran, Iran
[4] Chosun Univ, Dept Comp Engn, Gwangju, South Korea
[5] Shahid Beheshti Univ, Fac Comp Sci & Engn, GC, Tehran, Iran
[6] Shahid Beheshti Univ, Fac Math, Dept Comp & Data Sci, GC, Tehran, Iran
[7] Univ Waterloo, Dept Stat & Actuarial Sci, Waterloo, ON, Canada
关键词
Orthogonal polynomials; Hardware accelerator; FPGA; Embedded systems; EMDEN TYPE EQUATIONS; NEURAL-NETWORK; LEGENDRE POLYNOMIALS; OPERATIONAL MATRIX; KERNEL; APPROXIMATION; REALIZATION; DYNAMICS; MODEL;
D O I
10.1007/s00366-022-01612-x
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
There are many algorithms based on orthogonal functions that can be applied to real-world problems. For example, many of them can be reduced to approximate the solution of a dynamical system, and the approximation can be done with orthogonal functions. But calculating the orthogonal functions is very time-consuming, there are many difficulties in implementation of them and because of these drawbacks, they are not utilized in real applications. For the purpose of solving this issue and filling the gap between the theory and real applications, in this paper, an FPGA implementation of some classical orthogonal polynomials families is presented. Here, hardware architectures of the first and second kinds of Chebyshev, Jacobi, Legendre, Gegenbauer, Laguerre, and Hermit polynomials are presented. The experiments show that the presented architectures are low power, fast, and with a small circuit area. The obtained results show a 10.5x speed-up in the best case, 1.5x speed-up in the worst case, and at least 47% reduction in power consumption in comparison with the state-of-the-art hardware implementations. All implementations and codes are available at https://github.com/sampp098/forthopoly.
引用
收藏
页码:2257 / 2276
页数:20
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