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cs.DC2025
KV Cache Compression for Inference Efficiency in LLMs: A Review
Yanyu Liu, Jingying Fu, Sixiang Liu +4
Withtherapid advancement of large language models (LLMs), the context length for inference has been continuously increasing, leading to an exponential growth in the demand for Key-…
cs.DC2020★ 1 cited
HyperSched: Dynamic Resource Reallocation for Model Development on a Deadline
Richard Liaw, Romil Bhardwaj, Lisa Dunlap +4
Prior research in resource scheduling for machine learning training workloads has largely focused on minimizing job completion times. Commonly, these model training workloads colle…