SoroushVahidi/llm-serving-scheduler-baselines
LLM-Serving Scheduler Baselines: Simulation Performance Outcomes for Scheduler Policies This is a comprehensive, text-free, highly structured simulation results dataset for large language model (LLM) serving schedulers. It contains policy-level outcome records generated across synthetic scheduler stress tests and an added TraceLab-derived out-of-distribution policy sweep. The dataset compares 12 highly optimized third-party baseline schedulers against APT-Serve (a… See the full description on the dataset page: https://huggingface.co/datasets/SoroushVahidi/llm-serving-scheduler-baselines.
docs: expand evidence-based Limitations and Non-Intended Uses sections
docs: add Quickstart and cross-link to llm-serving-selector-regret
Add TraceLab OOD scheduler policy sweep
Fix published-state wording, add size_categories, disclose source-commit provenance gap
Fix published-state wording, add size_categories, disclose source-commit provenance gap
Publish v1 baseline simulated evaluation results
initial commit