Research progress on memristor: From synapses to computing systems
As the limits of transistor technology are approached, feature size in integrated circuit
transistors has been reduced very near to the minimum physically-realizable channel length …
transistors has been reduced very near to the minimum physically-realizable channel length …
On the thermal models for resistive random access memory circuit simulation
Resistive Random Access Memories (RRAMs) are based on resistive switching (RS)
operation and exhibit a set of technological features that make them ideal candidates for …
operation and exhibit a set of technological features that make them ideal candidates for …
Design of reliable DNN accelerator with un-reliable ReRAM
This paper presents an algorithmic approach to design reliable ReRAM based Processing-
in-Memory (PIM) architecture for Deep Neural Network (DNN) acceleration under intrinsic …
in-Memory (PIM) architecture for Deep Neural Network (DNN) acceleration under intrinsic …
The N3XT approach to energy-efficient abundant-data computing
The world's appetite for analyzing massive amounts of structured and unstructured data has
grown dramatically. The computational demands of these abundant-data applications, such …
grown dramatically. The computational demands of these abundant-data applications, such …
A modeling methodology for resistive ram based on stanford-pku model with extended multilevel capability
J Reuben, D Fey, C Wenger - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Modeling of resistive RAMs (RRAMs) is a herculean task due to its non-linearity. While the
exigent need for a model has motivated research groups to formulate realistic models, the …
exigent need for a model has motivated research groups to formulate realistic models, the …
Resistive RAM-centric computing: Design and modeling methodology
Memory-centric computing with on-chip nonvolatile memories provides unique opportunities
for native and local information processing in an energy-efficient manner. Design and …
for native and local information processing in an energy-efficient manner. Design and …
SPICE compact modeling of bipolar/unipolar memristor switching governed by electrical thresholds
F García-Redondo, RP Gowers… - … on Circuits and …, 2016 - ieeexplore.ieee.org
In this work, we propose a physical memristor/resistive switching device SPICE compact
model, that is able to accurately fit both unipolar/bipolar devices settling to its current-voltage …
model, that is able to accurately fit both unipolar/bipolar devices settling to its current-voltage …
Accurate inference with inaccurate rram devices: A joint algorithm-design solution
Resistive random access memory (RRAM) is a promising technology for energy-efficient
neuromorphic accelerators. However, when a pretrained deep neural network (DNN) model …
neuromorphic accelerators. However, when a pretrained deep neural network (DNN) model …
An atomistic model of field-induced resistive switching in valence change memory
In valence change memory (VCM) cells, the conductance of an insulating switching layer is
reversibly modulated by creating and redistributing point defects under an external field …
reversibly modulated by creating and redistributing point defects under an external field …
Neural-pim: Efficient processing-in-memory with neural approximation of peripherals
Processing-in-memory (PIM) architectures have demonstrated great potential in accelerating
numerous deep learning tasks. Particularly, resistive random-access memory (RRAM) …
numerous deep learning tasks. Particularly, resistive random-access memory (RRAM) …