Enhancing LoRA Model Serving Capacity via Adaptive Operator Scheduling for Multi-Tenancy on GPU
Low-Rank Adaptation (LoRA) has garnered increasing attention for effectively fine-tuning large language models (LLMs) with limited resources. Nonetheless, conventional approaches that cater to multiple LoRA models independently lead to redundant computations and suboptimal GPU utilization. This stud...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10721583/ |
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