2 papers
cs.DC2026
RLBoost: Harvesting Preemptible Resources for Cost-Efficient Reinforcement Learning on LLMs
Yongji Wu, Xueshen Liu, Haizhong Zheng +5
Reinforcement learning (RL) has become essential for unlocking advanced reasoning capabilities in large language models (LLMs). RL workflows involve interleaving rollout and traini…
cs.DC2025
Cortex: Workflow-Aware Resource Pooling and Scheduling for Agentic Serving
Nikos Pagonas, Yeounoh Chung, Kostis Kaffes +1
We introduce Cortex, a prototype workflow-aware serving platform designed for agentic workloads. The core principle of Cortex is stage isolation: it provisions dedicated resource p…