Journal
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2024 |
PF-GEMV: Utilization maximizing architecture in fast matrix–vector multiplication for GPT-2 inference
Hyeji Kim
ETRI Journal, v.46, no.5, pp.817-828 |
1 |
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Conference
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2024 |
EV-XF: Extension Framework for Training of Deep Neural Network with AI Processor Simulator
김혜지
반도체공학회 학술 대회 (하계) 2024, pp.76-77 |
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Conference
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2024 |
Tile Based Scalable K-Artificial Brain Processor for Large Neural Network Processing
여준기
대한전자공학회 학술 대회 (하계) 2024, pp.767-769 |
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Journal
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2023 |
Trends in Lightweight Neural Network Algorithms and Hardware Acceleration Technologies for Transformer-based Deep Neural Networks
김혜지
전자통신동향분석, v.38, no.5, pp.12-22 |
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Journal
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2023 |
Trends of DNN Training with Low-Precision Data Format for AI Processor
김혜지
주간기술동향, v.2080, pp.2-12 |
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Conference
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2022 |
M3FPU: Multiformat Matrix Multiplication FPU Architectures for Neural Network Computations
Won Jeon
International Conference on Artificial Intelligence Circuits and Systems (AICAS) 2022, pp.150-153 |
3 |
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Journal
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2022 |
Trends of Low-Precision Processing for AI Processor
김혜지
전자통신동향분석, v.37, no.1, pp.53-63 |
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Conference
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2021 |
Live Demonstration: A Neural Processor for AI Acceleration
Hyeji Kim
International Symposium on Circuits and Systems (ISCAS) 2021, pp.1-1 |
3 |
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Journal
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2021 |
Trends of Compiler Development for AI Processor
김진규
전자통신동향분석, v.36, no.2, pp.32-42 |
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