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cs.AR2026
Beacon: LLM Multi-Agent Driven Hardware Design Space Exploration for Heterogeneous Multi-Chiplet Deep Learning Accelerators
Boyu Li, Zongwei Zhu, Qianyue Cao +2
Heterogeneous multi-chiplet accelerators allow chiplets to be configured independently to better match different operator characteristics and improve inference efficiency. However,…
cs.AR2025
Compass: Co-Exploration of Mapping and Hardware for Heterogeneous Multi-Chiplet Accelerators Targeting LLM Inference Service Workloads
Boyu Li, Zongwei Zhu, Qianyue Cao +2
Large language models (LLMs) bring huge computational demands, which makes multi-chiplet accelerators that can integrate large-scale computing resources a powerful solution. Howeve…