A Year in LLM Serving: Workload Evolution, Caching and Load-Balancing

arXiv:2608.13573 · cs.AI · Submitted 2026-07-03 · Read on arXiv

cs.AI

Submitted: 2026-07-03

Updated: 2026-09-07

Code: https://github.com/HarvardMadSys/chutes_workload

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Trace — 53× in this paper · explained in 2 episodes
• Decode — 19× in this paper · explained in 2 episodes
• KV cache — 9× in this paper · explained in 3 episodes
• Large Language Model — 9× in this paper
• Agentic Workflows — 3× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 3 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Large Language Model (LLM) — 2× in this paper · explained in 3 episodes
• Symposium on Operating Systems Principles — 2× in this paper
• Transformer — 2× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• RAG — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Structural Constraints — 1× in this paper · explained in 2 episodes

Sources

• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• DeepSeek-V3 Technical Report
• LMCache: An Efficient KV Cache Layer for Enterprise-Scale LLM Inference
• ModServe: Modality- and Stage-Aware Resource Disaggregation for Scalable Multimodal Model Serving
• BurstGPT: A Real-world Workload Dataset to Optimize LLM Serving Systems
• ServeGen: Workload Characterization and Generation of Large Language Model Serving in Production
• WildChat: 1M ChatGPT Interaction Logs in the Wild
• LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

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