RT-MDM: Real-Time Scheduling Framework for Multi-DNN on MCU Using External Memory
Sukmin Kang, Seongtae Lee, Hyunwoo Koo, Hoon Sung Chwa, Jinkyu Lee
摘要
As the application scope of DNNs executed on microcontroller units (MCUs) extends to time-critical systems, it becomes important to ensure timing guarantees for increasing demand of DNN inferences. To this end, this paper proposes RT-MDM, the first Real-Time scheduling framework for Multiple DNN tasks executed on an MCU using external memory. Identifying execution-order dependencies among segmented DNN models and memory requirements for parallel execution subject to the dependencies, we propose (i) a segment-group-based memory management policy that achieves isolated memory usage within a segment group and sharded memory usage across different segment groups, and (ii) an intra-task scheduler specialized for the proposed policy. Implementing RT-MDM on an actual system and optimizing its parameters for DNN segmentation and segment-group mapping, we demonstrate the effectiveness of RT-MDM in accommodating more DNN tasks while providing their timing guarantees.
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它引用的顶会 Paper3
- LaLaRAND: Flexible Layer-by-Layer CPU/GPU Scheduling for Real-Time DNN TasksWoosung Kang, Kilho Lee, Jinkyu Lee, Insik Shin 等RTSS 2021 · 被引用 68 次
- Demand Layering for Real-Time DNN Inference with Minimized Memory UsageMingoo Ji, Saehanseul Yi, Changjin Koo, Sol Ahn 等RTSS 2022 · 被引用 21 次
- SPET: Transparent SRAM Allocation and Model Partitioning for Real-time DNN Tasks on Edge TPUChanghun Han, Hoon Sung Chwa, Kilho Lee, Sangeun OhDAC 2023 · 被引用 6 次
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