most citedPerfSAGE: Generalized Inference Performance Predictor for Arbitrary Deep Learning Models on Edge Devices

1 citations · 1 across the 1 of their papers we have counts for

collaborators

2 papers

cs.LG2023★ 1 cited

PerfSAGE: Generalized Inference Performance Predictor for Arbitrary Deep Learning Models on Edge Devices

Yuji Chai, Devashree Tripathy, Chuteng Zhou +6

The ability to accurately predict deep neural network (DNN) inference performance metrics, such as latency, power, and memory footprint, for an arbitrary DNN on a target hardware p…

cs.LG2022

UDC: Unified DNAS for Compressible TinyML Models

Igor Fedorov, Ramon Matas, Hokchhay Tann +3

Deploying TinyML models on low-cost IoT hardware is very challenging, due to limited device memory capacity. Neural processing unit (NPU) hardware address the memory challenge by u…