DARIS: An Oversubscribed Spatio-Temporal Scheduler for Real-Time DNN Inference on GPUs

The widespread use of Deep Neural Networks (DNNs) is limited by high computational demands, especially in constrained environments. GPUs, though effective accelerators, often face underutilization and rely on coarse-grained scheduling. This paper introduces DARIS, a priority-based real-time DNN sche...

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Bibliographic Details

Published in:	2025 62nd ACM/IEEE Design Automation Conference (DAC) pp. 1 - 7
Main Authors:	Babaei, Amir Fakhim, Chantem, Thidapat
Format:	Conference Proceeding
Language:	English
Published:	IEEE 22.06.2025
Subjects:	Artificial neural networks Design automation Faces Graphics processing units Processor scheduling Quality of service Real-time systems Synchronization Throughput Time factors
Online Access:	Get full text
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