Deterministic methods for stochastic computing using low-discrepancy sequences
Recently, deterministic approaches to stochastic computing (SC) have been proposed.
These compute with the same constructs as stochastic computing but operate on …
These compute with the same constructs as stochastic computing but operate on …
Stochastic computing in convolutional neural network implementation: A review
YY Lee, ZA Halim - PeerJ Computer Science, 2020 - peerj.com
Stochastic computing (SC) is an alternative computing domain for ubiquitous deterministic
computing whereby a single logic gate can perform the arithmetic operation by exploiting the …
computing whereby a single logic gate can perform the arithmetic operation by exploiting the …
An energy-efficient and noise-tolerant recurrent neural network using stochastic computing
Recurrent neural networks (RNNs) are widely used to solve a large class of recognition
problems, including prediction, machine translation, and speech recognition. The hardware …
problems, including prediction, machine translation, and speech recognition. The hardware …
Neural network classifiers using stochastic computing with a hardware-oriented approximate activation function
Neural networks are becoming prevalent in many areas, such as pattern recognition and
medical diagnosis. Stochastic computing is one potential solution for neural networks …
medical diagnosis. Stochastic computing is one potential solution for neural networks …
Stochastic computing in beyond von-neumann era: Processing bit-streams in memristive memory
Stochastic Computing (SC) is an alternative computing paradigm that promises high
robustness to noise and outstanding area-and power-efficiency compared to traditional …
robustness to noise and outstanding area-and power-efficiency compared to traditional …
Stochastic computing convolutional neural network architecture reinvented for highly efficient artificial intelligence workload on field-programmable gate array
YY Lee, ZA Halim, MNA Wahab, TA Almohamad - Research, 2024 - spj.science.org
Stochastic computing (SC) has a substantial amount of study on application-specific
integrated circuit (ASIC) design for artificial intelligence (AI) edge computing, especially the …
integrated circuit (ASIC) design for artificial intelligence (AI) edge computing, especially the …
An overview of time-based computing with stochastic constructs
Computing on time-based data is a recent evolution of research in stochastic computing. As
with stochastic computing, complex functions can be computed with remarkably low area …
with stochastic computing, complex functions can be computed with remarkably low area …
Design and analysis of efficient maximum/minimum circuits for stochastic computing
M Lunglmayr, D Wiesinger… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
In stochastic computing (SC), a real-valued number is represented by a stochastic bit
stream, encoding its value in the probability of obtaining a one. This leads to a significantly …
stream, encoding its value in the probability of obtaining a one. This leads to a significantly …
CORLD: In-stream correlation manipulation for low-discrepancy stochastic computing
Stochastic computing (SC) is a re-emerging computing paradigm providing low-cost and
noise-tolerant designs for a wide range of arithmetic operations. SC circuits operate on …
noise-tolerant designs for a wide range of arithmetic operations. SC circuits operate on …
Neural network classifiers using a hardware-based approximate activation function with a hybrid stochastic multiplier
Neural networks are becoming prevalent in many areas, such as pattern recognition and
medical diagnosis. Stochastic computing is one potential solution for neural networks …
medical diagnosis. Stochastic computing is one potential solution for neural networks …