Pubblicazioni

LO-SC: Local-Only Split Computing for Accurate Deep Learning on Edge Devices  (2025)

Autori:
Capogrosso, Luigi; Fraccaroli, Enrico; Cristani, Marco; Fummi, Franco; Chakraborty, Samarjit
Titolo:
LO-SC: Local-Only Split Computing for Accurate Deep Learning on Edge Devices
Anno:
2025
Tipologia prodotto:
Contributo in atti di convegno
Tipologia ANVUR:
Contributo in Atti di convegno
Lingua:
Inglese
Formato:
Elettronico
Titolo del Convegno:
38th International Conference on VLSI Design (VLSID)
Luogo:
Bangalore, India
Periodo:
04-08 January 2025
Intervallo pagine:
445-450
Parole chiave:
Deep Neural Networks; Edge Device
Breve descrizione dei contenuti:
Split Computing (SC) enables deploying a Deep Neural Network (DNN) on edge devices with limited resources by splitting the workload between the edge device and a remote server. However, relying on a server can be expensive, requires a reliable network, and introduces unpredictable latency. Existing solutions for on-device DNNs deployment often sacrifice accuracy for efficiency. In this paper, we study how to use the concepts from SC to split a DNN for executing on the same device without compromising accuracy. In other words, we propose Local-Only Split Computing (LO-SC), a new approach to split a DNN for execution entirely on the edge device while maintaining high accuracy and predictable latency. We formalize LO-SC as a MixedInteger Linear Problem (MILP) problem and solve it using a multi-constrained ordered knapsack algorithm. The proposed method achieves promising results on both synthetic and realworld data, offering a viable alternative for accurately deploying DNNs on resource-constrained edge devices. The source code is available at https://github.com/intelligolabs/LO-SC.
Pagina Web:
https://ieeexplore.ieee.org/abstract/document/10900702
Id prodotto:
144572
Handle IRIS:
11562/1156847
ultima modifica:
11 marzo 2025
Citazione bibliografica:
Capogrosso, Luigi; Fraccaroli, Enrico; Cristani, Marco; Fummi, Franco; Chakraborty, Samarjit, LO-SC: Local-Only Split Computing for Accurate Deep Learning on Edge Devices  in Proceedings of the 38th International Conference on VLSI Design (VLSID)Atti di "38th International Conference on VLSI Design (VLSID)" , Bangalore, India , 04-08 January 2025 , 2025pp. 445-450

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