Approximate computing: An emerging paradigm for energy-efficient design
J Han, M Orshansky - 2013 18th IEEE European Test …, 2013 - ieeexplore.ieee.org
Approximate computing has recently emerged as a promising approach to energy-efficient
design of digital systems. Approximate computing relies on the ability of many systems and …
design of digital systems. Approximate computing relies on the ability of many systems and …
Survey of stochastic computing
Stochastic computing (SC) was proposed in the 1960s as a low-cost alternative to
conventional binary computing. It is unique in that it represents and processes information in …
conventional binary computing. It is unique in that it represents and processes information in …
The promise and challenge of stochastic computing
Stochastic computing (SC) is an unconventional method of computation that treats data as
probabilities. Typically, each bit of an N-bit stochastic number (SN) Xis randomly chosen to …
probabilities. Typically, each bit of an N-bit stochastic number (SN) Xis randomly chosen to …
VLSI implementation of deep neural network using integral stochastic computing
A Ardakani, F Leduc-Primeau… - … Transactions on Very …, 2017 - ieeexplore.ieee.org
The hardware implementation of deep neural networks (DNNs) has recently received
tremendous attention: many applications in fact require high-speed operations that suit a …
tremendous attention: many applications in fact require high-speed operations that suit a …
[HTML][HTML] Skyrmionics—Computing and memory technologies based on topological excitations in magnets
Solitonic magnetic excitations such as domain walls and, specifically, skyrmionics enable
the possibility of compact, high density, ultrafast, all-electronic, low-energy devices, which is …
the possibility of compact, high density, ultrafast, all-electronic, low-energy devices, which is …
Skyrmion gas manipulation for probabilistic computing
The topologically protected magnetic spin configurations known as Skyrmions offer
promising applications due to their stability, mobility, and localization. We emphasize how to …
promising applications due to their stability, mobility, and localization. We emphasize how to …
Stochastic circuits for real-time image-processing applications
Real-time image-processing applications impose severe design constraints in terms of area
and power. Examples of interest include retinal implants for vision restoration and on-the-fly …
and power. Examples of interest include retinal implants for vision restoration and on-the-fly …
Computation on stochastic bit streams digital image processing case studies
Maintaining the reliability of integrated circuits as transistor sizes continue to shrink to
nanoscale dimensions is a significant looming challenge for the industry. Computation on …
nanoscale dimensions is a significant looming challenge for the industry. Computation on …
Energy-efficient hybrid stochastic-binary neural networks for near-sensor computing
Recent advances in neural networks (NNs) exhibit unprecedented success at transforming
large, unstructured data streams into compact higher-level semantic information for tasks …
large, unstructured data streams into compact higher-level semantic information for tasks …
Exploiting correlation in stochastic circuit design
Stochastic computing (SC) is a re-emerging computing paradigm which enables ultra-low
power and massive parallelism in important applications like real-time image processing. It …
power and massive parallelism in important applications like real-time image processing. It …