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Hardware implementation of memristor-based artificial neural networks
Artificial Intelligence (AI) is currently experiencing a bloom driven by deep learning (DL)
techniques, which rely on networks of connected simple computing units operating in …
techniques, which rely on networks of connected simple computing units operating in …
Spvit: Enabling faster vision transformers via latency-aware soft token pruning
Abstract Recently, Vision Transformer (ViT) has continuously established new milestones in
the computer vision field, while the high computation and memory cost makes its …
the computer vision field, while the high computation and memory cost makes its …
Forms: Fine-grained polarized reram-based in-situ computation for mixed-signal dnn accelerator
Recent work demonstrated the promise of using resistive random access memory (ReRAM)
as an emerging technology to perform inherently parallel analog domain in-situ matrix …
as an emerging technology to perform inherently parallel analog domain in-situ matrix …
Coordinated batching and DVFS for DNN inference on GPU accelerators
Employing hardware accelerators to improve the performance and energy-efficiency of DNN
applications is on the rise. One challenge of using hardware accelerators, including the GPU …
applications is on the rise. One challenge of using hardware accelerators, including the GPU …
[HTML][HTML] Modeling and simulating in-memory memristive deep learning systems: An overview of current efforts
C Lammie, W ** for reram-based edge ai
Recent research demonstrated the promise of using resistive random access memory
(ReRAM) as an emerging technology to perform inherently parallel analog domain in-situ …
(ReRAM) as an emerging technology to perform inherently parallel analog domain in-situ …
Memtorch: A simulation framework for deep memristive cross-bar architectures
Memristive devices arranged in cross-bar architectures have shown great promise to
facilitate the acceleration and improve the power efficiency of Deep Learning (DL) systems …
facilitate the acceleration and improve the power efficiency of Deep Learning (DL) systems …
Memristor-based light-weight transformer circuit implementation for speech recognizing
Transformer network (TN) is a promising model widely used for natural language processing
(NLP), computer vision (CV), and audio processing (AP). However, the large number of …
(NLP), computer vision (CV), and audio processing (AP). However, the large number of …