3 papers
cs.AI2026
ChipBench: A Next-Step Benchmark for Evaluating LLM Performance in AI-Aided Chip Design
Zhongkai Yu, Chenyang Zhou, Yichen Lin +6
While Large Language Models (LLMs) show significant potential in hardware engineering, current benchmarks suffer from saturation and limited task diversity, failing to reflect LLMs…
cs.AI2026
ScaleSim: Serving Large-Scale Multi-Agent Simulation with Invocation Distance-Based Memory Management
Zaifeng Pan, Yipeng Shen, Zhengding Hu +6
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-re…
cs.DC2025
KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads
Yue Guan, Yuanwei Fang, Keren Zhou +5
In this work, we propose KPerfIR, a novel multilevel compiler-centric infrastructure to enable the development of customizable, extendable, and portable profiling tools tailored fo…