AttentionLib: A Scalable Optimization Framework for Automated Attention Acceleration on FPGA

The self-attention mechanism is a fundamental component within transformer-based models. Nowadays, as the length of sequences processed by large language models (LLMs) continues to increase, the attention mechanism has gradually become a bottleneck in model inference. The LLM inference process can b...

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Veröffentlicht in:	Proceedings - Design, Automation, and Test in Europe Conference and Exhibition S. 1 - 7
Hauptverfasser:	Liu, Zhenyu, Zhou, Xilang, Sun, Faxian, Chen, Jianli, Yu, Jun, Wang, Kun
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	EDAA 31.03.2025
Schlagworte:	Attention mechanisms Computational modeling Engines Field programmable gate arrays FPGA Fusion Hardware HLS Manuals MLIR Optimization Scalability Space exploration Transformer Transformers
ISSN:	1558-1101
Online-Zugang:	Volltext
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