Neuromorphic Hardware Accelerators

Yadav, Pamul; Mishra, Ashutosh; Kim, Shiho

doi:10.1007/978-3-031-22170-5_8

Artificial Intelligence and Hardware Accelerators 2023

DOI: 10.1007/978-3-031-22170-5_8

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Neuromorphic Hardware Accelerators

Pamul Yadav

Ashutosh Mishra

Shiho Kim

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2024

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Cited by 1 publication

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Neuromorphic Software Tools and Development Environments

Sailaja,

Sharma,

Nune

2024

Advances in Computational Intelligence and Robotics

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We are seeing a technological transformation now that was unthinkable ten years ago. Although introducing artificial intelligence (AI) in contemporary business theoretically permits unrestricted expansion, the dreaded power-wall issue in the parallel computing paradigm prevents us from fully using AI's potential. Because they are expected to operate at extremely low power, modern Neuromorphic accelerators provide a profitable substitute for conventional artificial neural network (ANN) accelerators for deep learning (DL). Neuromorphic accelerators are centred on Spiking Neural Networks (SNN), which seek to mimic the extremely energy-efficient mechanism operating in our brains. This chapter covers the general overview of Neuromorphic software tools and development environments, including platforms, frameworks, and best practices.

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Neuromorphic Software Tools and Development Environments

Sailaja,

Sharma,

Nune

2024

Advances in Computational Intelligence and Robotics

View full text Add to dashboard Cite

show abstract

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Neuromorphic Hardware Accelerators

Cited by 1 publication

References 37 publications

Neuromorphic Software Tools and Development Environments

Neuromorphic Software Tools and Development Environments

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