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cs.AI2025
QuantuneV2: Compiler-Based Local Metric-Driven Mixed Precision Quantization for Practical Embedded AI Applications
Jeongseok Kim, Jemin Lee, Yongin Kwon +1
Mixed-precision quantization methods have been proposed to reduce model size while minimizing accuracy degradation. However, existing studies require retraining and do not consider…
cs.AI2024
LLMem: Estimating GPU Memory Usage for Fine-Tuning Pre-Trained LLMs
Taeho Kim, Yanming Wang, Vatshank Chaturvedi +4
Fine-tuning pre-trained large language models (LLMs) with limited hardware presents challenges due to GPU memory constraints. Various distributed fine-tuning methods have been prop…