✨LUT-LLM: Efficient Large Language Model Inference with Memory-based Computations on FPGAs

📝 Summary:
LUT-LLM is an FPGA accelerator for LLM inference that leverages on-chip memory to shift computation from arithmetic to memory-based operations via table lookups. This innovative approach achieves 1.66x lower latency than AMD MI210 and 1.72x higher energy efficiency than NVIDIA A100 for a 1.7B LLM.

🔹 Publication Date: Published on Nov 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.06174
• PDF: https://arxiv.org/pdf/2511.06174

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✓ https://xn--r1a.website/DataScienceT

#LLM #FPGA #AI #DeepLearning #AIHardware

✨Understand and Accelerate Memory Processing Pipeline for Disaggregated LLM Inference

📝 Summary:
LLM inference faces significant memory processing overhead. This paper proposes using heterogeneous GPU-FPGA systems to accelerate these operations by offloading memory-bounded tasks to FPGAs. This achieves 1.04-2.2x speedup and 1.11-4.7x energy savings over GPU baselines, proving heterogeneous s...

🔹 Publication Date: Published on Mar 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.29002
• PDF: https://arxiv.org/pdf/2603.29002

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For more data science resources:
✓ https://xn--r1a.website/DataScienceT

#LLMInference #FPGA #HeterogeneousComputing #HardwareAcceleration #SystemArchitecture