Author

Jongse Park

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Jul 2026

NELSSA: A GPU-PNM Heterogeneous System for Mixed-Length LLM Serving via Length-based Request Placement

NELSSA is presented, an LLM serving system that integrates GPUs with real-world Processing-near-Memory accelerator devices to efficiently support mixed-length workloads and improves decode throughput by up to 5.5x in tokens/sec and reduces P99 latency by up to 15x compared to GPU-only baselines.

Sookyung Choi, Seungyong Lee, Kangkyu Park et al. · arXiv.org · 0 citations

Preprint Aug 2026

Simthesizer: An Agent-Driven Simulation Framework for LLM Serving Systems

Simthesizer introduces a composable simulator infrastructure that uniformly expresses the complete serving workflow, including the control decisions that coordinate it, and realizes it as a unified dynamic graph in Simthesizer simulator.

Wonung Kim, Hyunmin Choi, Minsu Kim et al. · 0 citations