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This repository is a curated collection of research papers on machine learning systems, organized by topic into directories such as Checkpoint&Memory, Cluster Scheduling, Serving, and Training. Each directory contains PDF files of relevant papers, often accompanied by README.md files providing context or summaries. The repository serves as a reference literature review for researchers and practitioners in the field of ML systems, covering topics like checkpointing, cluster scheduling, model serving, training optimizations, and more. It does not contain any source code or executable components, focusing solely on disseminating academic research.
RATING:
MAINT: active
DRIFT: low
── end of results ──