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Deep neural networks (DNNs) are increasingly critical to embedded and cyber–physical systems that demand strict real-time guarantees. However, the computational intensity of modern DNNs often exceeds ...
Real-time systems
Worst-case execution time (WCET)
Deterministic scheduling
Distributed deep neural network inference
Heterogeneous multiprocessor scheduling
Directed acyclic graph (DAG) scheduling
Time-Sensitive Networking (TSN)
FPGA-based acceleration
