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Hsiao et al., 2019 - Google Patents

Multi-Precision Table-Addition Designs for Computing Nonlinear Functions in Deep Neural Networks

Hsiao et al., 2019

Document ID
17081818277114222900
Author
Hsiao S
Huang K
Chen Y
Publication year
Publication venue
2019 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)

External Links

Snippet

Computation of non-linear functions such as hyperbolic tangent and sigmoid is critical in machine learning. Furthermore, precision requirement varies across different layers in deep neural networks. Thus it is beneficial to design multi-precision function computation units …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

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    • G06F7/38—Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation
    • G06F7/48—Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation using non-contact-making devices, e.g. tube, solid state device; using unspecified devices
    • G06F7/52—Multiplying; Dividing
    • G06F7/535—Dividing only
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    • G06F7/52—Multiplying; Dividing
    • G06F7/523—Multiplying only
    • G06F7/53—Multiplying only in parallel-parallel fashion, i.e. both operands being entered in parallel
    • G06F7/5318—Multiplying only in parallel-parallel fashion, i.e. both operands being entered in parallel with column wise addition of partial products, e.g. using Wallace tree, Dadda counters
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    • G06F7/52—Multiplying; Dividing
    • G06F7/523—Multiplying only
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    • G06F7/5334—Reduction of the number of iteration steps or stages, e.g. using the Booth algorithm, log-sum, odd-even by using multiple bit scanning, i.e. by decoding groups of successive multiplier bits in order to select an appropriate precalculated multiple of the multiplicand as a partial product
    • G06F7/5336—Reduction of the number of iteration steps or stages, e.g. using the Booth algorithm, log-sum, odd-even by using multiple bit scanning, i.e. by decoding groups of successive multiplier bits in order to select an appropriate precalculated multiple of the multiplicand as a partial product overlapped, i.e. with successive bitgroups sharing one or more bits being recoded into signed digit representation, e.g. using the Modified Booth Algorithm
    • G—PHYSICS
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    • G06F7/544—Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation using non-contact-making devices, e.g. tube, solid state device; using unspecified devices for evaluating functions by calculation
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    • G06F7/483—Computations with numbers represented by a non-linear combination of denominational numbers, e.g. rational numbers, logarithmic number system, floating-point numbers
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    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
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    • G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
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    • G06F1/02—Digital function generators
    • G06F1/03—Digital function generators working, at least partly, by table look-up
    • G06F1/0307—Logarithmic or exponential functions

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