FLAME models layer-wise overlapping parallelism and asynchronous CPU-GPU pipeline bubbles to estimate inference latency across frequencies with sparse profiling and low error for DNNs and SLMs.
Rt-mdl: Supporting real-time mixed deep learning tasks on edge platforms
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Taming Asynchronous CPU-GPU Coupling for Frequency-aware Latency Estimation on Mobile Edge
FLAME models layer-wise overlapping parallelism and asynchronous CPU-GPU pipeline bubbles to estimate inference latency across frequencies with sparse profiling and low error for DNNs and SLMs.