Scalable and Energy-Efficient NN Acceleration with GPU-ReRAM Architecture

Moura, Rafael Fão de; Carro, Luigi

doi:10.1007/978-3-031-42921-7_16

Cited by 1 publication

(1 citation statement)

References 34 publications

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“…Redundancy is a key principle being employed, wherein critical components are duplicated to provide a backup in case of failure. Additionally, rigorous testing protocols and real-world simulations are integral to ensuring the robustness of AICAS, helping to identify and mitigate potential vulnerabilities before deployment [136][137][138].…”

Section: Robustness and Reliabilitymentioning

confidence: 99%

Advancements in Artificial Intelligence Circuits and Systems (AICAS)

Miller,

Durlik,

Kostecka

et al. 2023

Electronics

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In the rapidly evolving landscape of electronics, Artificial Intelligence Circuits and Systems (AICAS) stand out as a groundbreaking frontier. This review provides an exhaustive examination of the advancements in AICAS, tracing its development from inception to its modern-day applications. Beginning with the foundational principles that underpin AICAS, we delve into the state-of-the-art architectures and design paradigms that are propelling the field forward. This review also sheds light on the multifaceted applications of AICAS, from optimizing energy efficiency in electronic devices to empowering next-generation cognitive computing systems. Key challenges, such as scalability and robustness, are discussed in depth, along with potential solutions and emerging trends that promise to shape the future of AICAS. By offering a comprehensive overview of the current state and potential trajectory of AICAS, this review serves as a valuable resource for researchers, engineers, and industry professionals looking to harness the power of AI in electronics.

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Section: Robustness and Reliabilitymentioning

confidence: 99%