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Circuits to Systems: Codesigning Efficient AI Hardware
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PRE
AI
DOI：10.1109/MDAT.2025.3600328.png)
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Abstract
En 中文
Editor's notes: The authors explore the intertwined progress of circuit innovation and system architecture that has propelled AI development-from early neuro-morphic circuits to today's memory-centric accelerators. They review milestones such as processing-in-memory, GPUs, and systolic arrays and address emerging challenges from large language models. -Jorg Henkel, Vice-President of Publications, IEEE CEDA -L. Miguel Silveira, President, IEEE CEDA
Keywords:
Artificial intelligence
Hardware
Computer architecture
Graphics processing units
Quantization (signal)
Training
Systolic arrays
Deep learning
Computational modeling
Architecture
Circuit synthesis
Circuits
Systems
Co-design
Neuromorphic Computing
AI Acceleration
Large Language Models
Journal
I
IF:
1.9
Papers:
39
Citations:
0
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Cited Papers
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