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Implementing spiking neural networks on neuromorphic architectures: A review
PK Huynh, ML Varshika, A Paul, M Isik, A Balaji… - ar** study
A Rautakoura, T Hämäläinen - ACM transactions on embedded …, 2023 - dl.acm.org
The success of agile development methods in software development has raised interest in
System-on-Chip (SoC) design, which involves high architectural and development process …
System-on-Chip (SoC) design, which involves high architectural and development process …
Opencgra: Democratizing coarse-grained reconfigurable arrays
C Tan, NB Agostini, J Zhang, M Minutoli… - 2021 IEEE 32nd …, 2021 - ieeexplore.ieee.org
Reconfigurable architectures are today experiencing a renewed interest for their ability to
provide specialization without sacrificing the capability to adapt to disparate workloads …
provide specialization without sacrificing the capability to adapt to disparate workloads …
From cnn to dnn hardware accelerators: A survey on design, exploration, simulation, and frameworks
LR Juracy, R Garibotti, FG Moraes - Foundations and Trends® …, 2023 - nowpublishers.com
Over the past decade, a massive proliferation of machine learning algorithms has emerged,
from applications for surveillance to self-driving cars. The turning point occurred with the …
from applications for surveillance to self-driving cars. The turning point occurred with the …
Automated generation of integrated digital and spiking neuromorphic machine learning accelerators
S Curzel, NB Agostini, S Song, I Dagli… - 2021 IEEE/ACM …, 2021 - ieeexplore.ieee.org
The growing numbers of application areas for artificial intelligence (AI) methods have led to
an explosion in availability of domain-specific accelerators, which struggle to support every …
an explosion in availability of domain-specific accelerators, which struggle to support every …
Special session: Towards an agile design methodology for efficient, reliable, and secure ML systems
S Dave, A Marchisio, MA Hanif… - 2022 IEEE 40th VLSI …, 2022 - ieeexplore.ieee.org
The real-world use cases of Machine Learning (ML) have exploded over the past few years.
However, the current computing infrastructure is insufficient to support all real-world …
However, the current computing infrastructure is insufficient to support all real-world …
Energy-efficient hardware acceleration of shallow machine learning applications
Z Zeng, SS Sapatnekar - 2023 Design, Automation & Test in …, 2023 - ieeexplore.ieee.org
ML accelerators have largely focused on building general platforms for deep neural
networks (DNNs), but less so on shallow machine learning (SML) algorithms. This paper …
networks (DNNs), but less so on shallow machine learning (SML) algorithms. This paper …
Agile-aes: Implementation of configurable aes primitive with agile design approach
X Guo, M El-Hadedy, S Mosanu, X Wei, K Skadron… - Integration, 2022 - Elsevier
In the data-centric era, interconnected devices must be able to communicate efficiently and
securely with their hosts even over untrusted networks. This led to the adoption of several …
securely with their hosts even over untrusted networks. This led to the adoption of several …
End-to-end synthesis of dynamically controlled machine learning accelerators
S Curzel, NB Agostini, VG Castellana… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Edge systems are required to autonomously make real-time decisions based on large
quantities of input data under strict power, performance, area, and other constraints. Meeting …
quantities of input data under strict power, performance, area, and other constraints. Meeting …
Smart sensors using artificial intelligence for on-detector electronics and ASICs
G Carini, G Deptuch, J Dickinson, D Doering… - arxiv preprint arxiv …, 2022 - arxiv.org
Cutting edge detectors push sensing technology by further improving spatial and temporal
resolution, increasing detector area and volume, and generally reducing backgrounds and …
resolution, increasing detector area and volume, and generally reducing backgrounds and …