UrgenGo: 自動運転向けの緊急度を考慮した透過的GPUカーネル起動
UrgenGo: Urgency-Aware Transparent GPU Kernel Launching for Autonomous Driving
アプリのソースコードやGPUドライバに手を加えず、カーネル起動を透過的に操作して緊急度の高いGPUタスクを優先するスケジューラを提案し、自動運転バスでの実証でデッドライン違反を61%削減した。
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著者: Hanqi Zhu, Wuyang Zhang, Xinran Zhang, Ziyang Tao, Xinrui Lin, Yu Zhang, Jianmin Ji, Yanyong Zhang
分類: cs.OS, cs.RO
原文アブストラクト
The rapid advancements in autonomous driving have introduced increasingly complex, real-time GPU-bound tasks critical for reliable vehicle operation. However, the proprietary nature of these autonomous systems and closed-source GPU drivers hinder fine-grained control over GPU executions, often resulting in missed deadlines that compromise vehicle performance. To address this, we present UrgenGo, a non-intrusive, urgency-aware GPU scheduling system that operates without access to application source code. UrgenGo implicitly prioritizes GPU executions through transparent kernel launch manipulation, employing task-level stream binding, delayed kernel launching, and batched kernel launch synchronization. We conducted extensive real-world evaluations in collaboration with a self-driving startup, developing 11 GPU-bound task chains for a realistic autonomous navigation application and implementing our system on a self-driving bus. Our results show a significant 61% reduction in the overall deadline miss ratio, compared to the state-of-the-art GPU scheduler that requires source code modifications.
