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zhongkai yu

2 accepted papers

2026

ScaleSim: Serving Large-Scale Multi-Agent Simulation with Invocation Distance-Based Memory Management

ICML 2026poster

LLM-based multi-agent simulations are increasingly adopted across application domains, but remain difficult to scale due to GPU memory pressure. Each agent maintains private GPU-resident states, including models, prefix caches, and adapters, which quickly exhaust device memory as the agent count gro…

Cited by 0SourceScholar
2026

TritonGym: A Benchmark for Agentic LLM Workflows in Triton GPU Code Generation

ICML 2026poster

Large language models (LLMs) can already draft plausible Triton kernels, yet most existing evaluations still focus on single-shot generation and underplay tool use and feedback. We introduce *TritonGym*, a benchmark and orchestration framework for evaluating agentic workflows in GPU code generation.…

Cited by 0SourceScholar