Gmlake Asplos 2025 Lexus. Hozier San Francisco 2025 Lexus James Paige 据悉，这篇名为《GMLake: Efficient and Transparent GPU Memory Defragmentation for Large-scale DNN Training with Virtual Memory Stitching》的研究成果，针对业界普遍存在的大模型训练显存效率问题. [2024.10] We release LayerKV arxiv, efficient CPU-GPU KV Cache management to decrease TTFT
2025 Lexus ES holds the line for 43,190 from www.motorauthority.com
[2024.05] GLake overview and recent update is presented on AICon 2024 (in Beijing, China, 2024-05-17) here [2024.05] The presentation slides in ASPLOS'24 can be found here GMLake is completely transparent to the DNN models and memory reduction techniques and ensures the seamless execution of resource-intensive deep-learning tasks.
2025 Lexus ES holds the line for 43,190
GMLake When there is no contineous free buffer to satisfy allocation requests, GMLake will return a complete buffer to users by combining multiple memory fragementation GMLake: Efficient and Transparent GPU Memory Defragmentation GMLake can reduce an average of 9.2 GB (up to 25 GB) GPU memory usage and 15% (up to 33% ) fragmentation among eight LLM models on GPU A100 with 80 GB memory
2025 Lexus ES holds the line for 43,190. [2024.07] We release vTensor, our LLM serving and KV Cache management system using VMM technique GMLake is completely transparent to the DNN models and memory reduction techniques and ensures the seamless execution of resource-intensive deep-learning tasks.
Itinerario Bsn 2025 Lexus Megan Butler. [2024.05] GLake overview and recent update is presented on AICon 2024 (in Beijing, China, 2024-05-17) here [2024.05] The presentation slides in ASPLOS'24 can be found here ASPLOS '24: Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2