[HTML][HTML] Analog architectures for neural network acceleration based on non-volatile memory
Analog hardware accelerators, which perform computation within a dense memory array,
have the potential to overcome the major bottlenecks faced by digital hardware for data …
have the potential to overcome the major bottlenecks faced by digital hardware for data …
The next generation of deep learning hardware: Analog computing
Initially developed for gaming and 3-D rendering, graphics processing units (GPUs) were
recognized to be a good fit to accelerate deep learning training. Its simple mathematical …
recognized to be a good fit to accelerate deep learning training. Its simple mathematical …
A 24–72-GS/s 8-b time-interleaved SAR ADC with 2.0–3.3-pJ/conversion and> 30 dB SNDR at Nyquist in 14-nm CMOS FinFET
A 24-72-GS/s 8-b time-interleaved analog-to-digital converter (ADC) is presented which
exceeds 39-dB SNDR at low input frequency and 30-dB SNDR at Nyquist. High SNDR at …
exceeds 39-dB SNDR at low input frequency and 30-dB SNDR at Nyquist. High SNDR at …
MNSIM 2.0: A behavior-level modeling tool for memristor-based neuromorphic computing systems
Memristor based neuromorphic computing systems give alternative solutions to boost the
computing energy efficiency of Neural Network (NN) algorithms. Because of the large-scale …
computing energy efficiency of Neural Network (NN) algorithms. Because of the large-scale …
A configurable multi-precision CNN computing framework based on single bit RRAM
Convolutional Neural Networks (CNNs) play a vital role in machine learning. Emerging
resistive random-access memories (RRAMs) and RRAM-based Processing-In-Memory …
resistive random-access memories (RRAMs) and RRAM-based Processing-In-Memory …
Single-shot optical neural network
Analog optical and electronic hardware has emerged as a promising alternative to digital
electronics to improve the efficiency of deep neural networks (DNNs). However, previous …
electronics to improve the efficiency of deep neural networks (DNNs). However, previous …
Enabling scientific computing on memristive accelerators
Linear algebra is ubiquitous across virtually every field of science and engineering, from
climate modeling to macroeconomics. This ubiquity makes linear algebra a prime candidate …
climate modeling to macroeconomics. This ubiquity makes linear algebra a prime candidate …
A 1.25-GS/s 7-b SAR ADC with 36.4-dB SNDR at 5 GHz using switch-bootstrapping, USPC DAC and triple-tail comparator in 28-nm CMOS
AT Ramkaj, M Strackx, MSJ Steyaert… - IEEE Journal of Solid …, 2018 - ieeexplore.ieee.org
This paper presents a 1.25-GS/s 7-b single-channel successive approximation register
(SAR) analog-to-digital converter (ADC) that achieves a low input frequency SNDR/SFDR of …
(SAR) analog-to-digital converter (ADC) that achieves a low input frequency SNDR/SFDR of …
A 10-mW 10-ENoB 1-GS/s ring-amp-based pipelined TI-SAR ADC with split MDAC and switched reference decoupling capacitor
This article presents a 12-bit 1-GS/s ring-amp-based analog-to-digital converter (ADC) with
a pipelined and time-interleaved successive approximation register (TI-SAR) hybrid …
a pipelined and time-interleaved successive approximation register (TI-SAR) hybrid …
A single-channel, 600-MS/s, 12-b, ringamp-based pipelined ADC in 28-nm CMOS
Achieving high linearity and bandwidth with good power efficiency makes the design of
ADCs in deep nanoscale CMOS processes very challenging, as the constraints of low …
ADCs in deep nanoscale CMOS processes very challenging, as the constraints of low …