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Application of the residue number system to reduce hardware costs of the convolutional neural network implementation
Convolutional neural networks are a promising tool for solving the problem of pattern
recognition. Most well-known convolutional neural networks implementations require a …
recognition. Most well-known convolutional neural networks implementations require a …
A framework for intelligence and cortical function based on grid cells in the neocortex
How the neocortex works is a mystery. In this paper we propose a novel framework for
understanding its function. Grid cells are neurons in the entorhinal cortex that represent the …
understanding its function. Grid cells are neurons in the entorhinal cortex that represent the …
Secure nearest neighbor revisited
In this paper, we investigate the secure nearest neighbor (SNN) problem, in which a client
issues an encrypted query point E (q) to a cloud service provider and asks for an encrypted …
issues an encrypted query point E (q) to a cloud service provider and asks for an encrypted …
Privft: Private and fast text classification with homomorphic encryption
We present an efficient and non-interactive method for Text Classification while preserving
the privacy of the content using Fully Homomorphic Encryption (FHE). Our solution (named …
the privacy of the content using Fully Homomorphic Encryption (FHE). Our solution (named …
Residue number systems: A new paradigm to datapath optimization for low-power and high-performance digital signal processing applications
Residue Number System (RNS) is a non-weighted number system which was proposed by
Garner back in 1959 to achieve fast implementation of addition, subtraction and …
Garner back in 1959 to achieve fast implementation of addition, subtraction and …
Single image motion deblurring using transparency
One of the key problems of restoring a degraded image from motion blur is the estimation of
the unknown shift-invariant linear blur filter. Several algorithms have been proposed using …
the unknown shift-invariant linear blur filter. Several algorithms have been proposed using …
High-performance FV somewhat homomorphic encryption on GPUs: An implementation using CUDA
Homomorphic encryption (HE) offers great capabilities that can solve a wide range of
privacy-preserving computing problems. This tool allows anyone to process encrypted data …
privacy-preserving computing problems. This tool allows anyone to process encrypted data …
Research challenges in next-generation residue number system architectures
The carry-free nature of residue number system (RNS) has introduced it as an efficient
unconventional number system which has attracted lots of researchers for many decades …
unconventional number system which has attracted lots of researchers for many decades …
High-performance computing based on residue number system: a review
V Balajishanmugam - 2023 9th International Conference on …, 2023 - ieeexplore.ieee.org
The speed of arithmetic operation is associated with the quantity of the numbers involved.
Residue Number System (RNS) is used to characterize a more significant numeral using a …
Residue Number System (RNS) is used to characterize a more significant numeral using a …
Res-DNN: A residue number system-based DNN accelerator unit
In this article, a technique, based on using Residue Number System (RNS) is suggested to
improve the energy efficiency of Deep Neural Networks (DNNs). In the DNN architecture …
improve the energy efficiency of Deep Neural Networks (DNNs). In the DNN architecture …