FPGA Implementation of Neuron Model Using Piecewise Nonlinear Function on Double-Precision Floating-Point Format

Kawamura, Satoshi; Saito, Masato; Yoshida, Hitoaki

doi:10.1007/978-3-319-42007-3_54

Cited by 1 publication

(2 citation statements)

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“…In the first case, the design optimization depends on the type of memories available in the device; in the second case, it is possible to develop logical simplifications. Other approximation form is the Piece Wise Lineal (PWL), which approaches each section with a straight line, in this case a multiplication and a sum are necessary [18,19,21,38,44,45,63,66,68,69,70].…”

Section: State Of the Art Of Hardware Implementation For Sigmoidal Fumentioning

confidence: 99%

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Fixed-point design methodology of the hyperbolic tangent function using lookup tables with performance evaluation on FPGA

Suárez¹

2018

EasyChair Preprints

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The sigmoid functions, including the hyperbolic tangent, are widely used in artificial neural networks. Usually, artificial neural networks are implemented on a computer, in training and testing phases, using floating point arithmetic. In some situations it is necessary to improve the performance of neural networks, in such cases the implementations are designed for specific digital devices, using fixed point arithmetic. This strategy increases the speed, and reduces the hardware resources and consumed power. The sigmoid functions are non-linear systems because include exponentials and divisions operations, so they are the bottleneck of the artificial neuron design and cannot be implemented directly in fixed-point format. For this reason, several methods of approximation are used, mainly based on piecewise approximations. One of the most common technique is to use Look-up Tables, which store samples of the function. This method needs a lot of hardware resources, but it reaches the highest speed. The first objective, using lookup table approximations, is to explore the set of solutions and study the effect of the number of bits. This can only be achieved if an advanced design methodology is used for experimentation, a second objective is to expose this fast and flexible design method. Thirdly, the measure of functionality associated with the error is reviewed. A new functionality measure is proposed associated with the concept of signal to noise power relation. The new measure allows compare different approximations; besides, some linearities are observed against the number of bits. Afterwards, the implementations are developed on some Field Programmable Gate Arrays and the performances are evaluated: hardware resources, speed and consumed power. Again, some linear behaviours are observed. Finally, a quality factor is proposed, which includes functionality and physical performances, this factor allows comparison between different implementations.

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Section: State Of the Art Of Hardware Implementation For Sigmoidal Fumentioning

confidence: 99%

“…Floating point arithmetic can be used on digital devices, but these operations need a high number of clock cycles [41], great consumption of power and hardware resources [42][43][44][45]. However, floating point numerical representation has a wide range with a good resolution [46,47].…”

Section: Introductionmentioning

confidence: 99%

Fixed-point design methodology of the hyperbolic tangent function using lookup tables with performance evaluation on FPGA

Suárez¹

2018

EasyChair Preprints

View full text Add to dashboard Cite

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FPGA Implementation of Neuron Model Using Piecewise Nonlinear Function on Double-Precision Floating-Point Format

Cited by 1 publication

References 6 publications

Fixed-point design methodology of the hyperbolic tangent function using lookup tables with performance evaluation on FPGA

Fixed-point design methodology of the hyperbolic tangent function using lookup tables with performance evaluation on FPGA

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