Weight-oriented approximation for energy-efficient neural network inference accelerators
Current research in the area of Neural Networks (NN) has resulted in performance
advancements for a variety of complex problems. Especially, embedded system applications …
advancements for a variety of complex problems. Especially, embedded system applications …
Approximate computing for ML: State-of-the-art, challenges and visions
In this paper, we present our state-of-the-art approximate techniques that cover the main
pillars of approximate computing research. Our analysis considers both static and …
pillars of approximate computing research. Our analysis considers both static and …
Design automation of approximate circuits with runtime reconfigurable accuracy
Leveraging the inherent error tolerance of a vast number of application domains that are
rapidly growing, approximate computing arises as a design alternative to improve the …
rapidly growing, approximate computing arises as a design alternative to improve the …
Circuit-level techniques for logic and memory blocks in approximate computing systemsx
This article presents an overview of circuit-level techniques used for approximate computing
(AC), including both computation and data storage units. After providing some background …
(AC), including both computation and data storage units. After providing some background …
A cross-layer gate-level-to-application co-simulation for design space exploration of approximate circuits in HEVC video encoders
A cross-layer design space exploration (DSE) method based on a proposed co-simulation
technique is presented herein. The proposed method is demonstrated evaluating the …
technique is presented herein. The proposed method is demonstrated evaluating the …
Approximate computing and the efficient machine learning expedition
Approximate computing (AxC) has been long accepted as a design alternative for efficient
system implementation at the cost of relaxed accuracy requirements. Despite the AxC …
system implementation at the cost of relaxed accuracy requirements. Despite the AxC …
On the resiliency of NCFET circuits against voltage over-scaling
Approximate computing is established as a design alternative to improve the energy
requirements of a vast number of applications, leveraging their intrinsic error tolerance …
requirements of a vast number of applications, leveraging their intrinsic error tolerance …
Thermal-aware design for approximate DNN accelerators
Recent breakthroughs in Neural Networks (NNs) have made DNN accelerators ubiquitous
and led to an ever-increasing quest on adopting them from Cloud to edge computing …
and led to an ever-increasing quest on adopting them from Cloud to edge computing …
Model-to-circuit cross-approximation for printed machine learning classifiers
Printed electronics (PEs) promises on-demand fabrication, low nonrecurring engineering
costs, and subcent fabrication costs. It also allows for high customization that would be …
costs, and subcent fabrication costs. It also allows for high customization that would be …
Deep-PowerX: A deep learning-based framework for low-power approximate logic synthesis
This paper aims at integrating three powerful techniques namely Deep Learning,
Approximate Computing, and Low Power Design into a strategy to optimize logic at the …
Approximate Computing, and Low Power Design into a strategy to optimize logic at the …