CAP
发表于 2025-3-21 19:57:42
书目名称Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0307903<br><br> <br><br>书目名称Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0307903<br><br> <br><br>书目名称Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0307903<br><br> <br><br>书目名称Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0307903<br><br> <br><br>书目名称Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0307903<br><br> <br><br>书目名称Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0307903<br><br> <br><br>书目名称Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0307903<br><br> <br><br>书目名称Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0307903<br><br> <br><br>书目名称Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0307903<br><br> <br><br>书目名称Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0307903<br><br> <br><br>
Foreshadow
发表于 2025-3-21 21:21:06
https://doi.org/10.1007/978-3-662-68073-5 neural networks can be accelerated in an energy-efficient manner. In particular, we focus on design considerations and trade-offs for mapping CNNs, Transformers, and GNNs on AI accelerators that attempt to maximize compute efficiency and minimize energy consumption by reducing the number of access to memory through efficient data reuse.
遗传
发表于 2025-3-22 03:22:25
https://doi.org/10.1007/978-3-8349-9996-2are. Thereafter, we discuss different interconnect techniques for IMC architectures proposed in the literature. Finally, different performance evaluation techniques for IMC architectures are described. We conclude the chapter with a summary and future avenues for IMC architectures for ML acceleration.
陶醉
发表于 2025-3-22 06:02:10
Low- and Mixed-Precision Inference Acceleratorsd, all aiming at enabling neural network inference at the edge. In this chapter, design choices and their implications on the flexibility and energy efficiency of several accelerators supporting extremely quantized networks are reviewed.
filicide
发表于 2025-3-22 12:15:42
http://reply.papertrans.cn/31/3080/307903/307903_5.png
圆柱
发表于 2025-3-22 14:27:08
In-Memory Computing for AI Accelerators: Challenges and Solutionsare. Thereafter, we discuss different interconnect techniques for IMC architectures proposed in the literature. Finally, different performance evaluation techniques for IMC architectures are described. We conclude the chapter with a summary and future avenues for IMC architectures for ML acceleration.
圆柱
发表于 2025-3-22 19:18:15
http://reply.papertrans.cn/31/3080/307903/307903_7.png
生命
发表于 2025-3-23 00:56:32
http://reply.papertrans.cn/31/3080/307903/307903_8.png
Cryptic
发表于 2025-3-23 02:50:56
http://reply.papertrans.cn/31/3080/307903/307903_9.png
挣扎
发表于 2025-3-23 07:20:08
Embedded Machine Learning for Cyber-Physical, IoT, and Edge ComputingHardware Architectur