Hardware and software optimizations for accelerating deep neural networks: Survey of current trends, challenges, and the road ahead
Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning
(DL) is already present in many applications ranging from computer vision for medicine to …
(DL) is already present in many applications ranging from computer vision for medicine to …
Weight-oriented approximation for energy-efficient neural network inference accelerators
ZG Tasoulas, G Zervakis… - … on Circuits and …, 2020 - ieeexplore.ieee.org
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 …
Libraries of approximate circuits: Automated design and application in CNN accelerators
Libraries of approximate circuits are composed of fully characterized digital circuits that can
be used as building blocks of energy-efficient implementations of hardware accelerators …
be used as building blocks of energy-efficient implementations of hardware accelerators …
Design of approximate booth squarer for error-tolerant computing
To explore the benefits of approximate computing, this article proposes an approximate
partial product generator for squarer (APPGS). Using APPGS, three designs of approximate …
partial product generator for squarer (APPGS). Using APPGS, three designs of approximate …
Red-cane: A systematic methodology for resilience analysis and design of capsule networks under approximations
A Marchisio, V Mrazek, MA Hanif… - … Design, Automation & …, 2020 - ieeexplore.ieee.org
Recent advances in Capsule Networks (CapsNets) have shown their superior learning
capability, compared to the traditional Convolutional Neural Networks (CNNs). However, the …
capability, compared to the traditional Convolutional Neural Networks (CNNs). However, the …
Resistive crossbar-aware neural network design and optimization
Recent research in Non-Volatile Memory (NVM) and Processing-in-Memory (PIM)
technologies has proposed low energy PIM-based system designs for high-performance …
technologies has proposed low energy PIM-based system designs for high-performance …
[PDF][PDF] Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead
M SHAFIQUE - arxiv.org
ABSTRACT Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep
Learning (DL) is already present in many applications ranging from computer vision for …
Learning (DL) is already present in many applications ranging from computer vision for …
[PDF][PDF] Approximating Deep Convolutional Neural Networks through Bit-level Masking of Network Parameters
GM Sarda - 2020 - webthesis.biblio.polito.it
POLITECNICO DI TORINO Page 1 POLITECNICO DI TORINO Master’s Degree in
Electronic Systems Master’s Degree Thesis Approximating Deep Convolutional Neural …
Electronic Systems Master’s Degree Thesis Approximating Deep Convolutional Neural …