AGENTSERVESIM is a new simulator that models multi-turn LLM agent serving at program granularity and reproduces real-system performance within 6% error on commodity CPUs.
arXiv:2602.23036 [cs]
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
years
2026 4verdicts
UNVERDICTED 4representative citing papers
Frontier is a new discrete-event simulator for disaggregated LLM serving that incorporates co-location, PDD, AFD, and optimizations, achieving under 4% throughput error and large reductions in latency prediction error versus prior simulators.
EnergyLens predicts multi-GPU LLM inference energy consumption with 9-13% MAPE and identifies configurations with up to 52x energy efficiency differences.
ASTRA-sim 3.0 introduces cache-line load-store simulation, a detailed GPU execution model, and InfraGraph to support high-fidelity distributed machine learning infrastructure simulations.
citing papers explorer
-
AGENTSERVESIM: A Hardware-aware Simulator for Multi-Turn LLM Agent Serving
AGENTSERVESIM is a new simulator that models multi-turn LLM agent serving at program granularity and reproduces real-system performance within 6% error on commodity CPUs.
-
Frontier: Towards Comprehensive and Accurate LLM Inference Simulation
Frontier is a new discrete-event simulator for disaggregated LLM serving that incorporates co-location, PDD, AFD, and optimizations, achieving under 4% throughput error and large reductions in latency prediction error versus prior simulators.
-
EnergyLens: Predictive Energy-Aware Exploration for Multi-GPU LLM Inference Optimization
EnergyLens predicts multi-GPU LLM inference energy consumption with 9-13% MAPE and identifies configurations with up to 52x energy efficiency differences.
-
ASTRA-sim 3.0: Next-Level Distributed Machine Learning Simulations via High-Fidelity GPU and Infrastructure Modeling
ASTRA-sim 3.0 introduces cache-line load-store simulation, a detailed GPU execution model, and InfraGraph to support high-fidelity distributed machine learning infrastructure simulations.