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by Jinse Kwon on 2020-01-02 18:04:34

Date : 2020. 01. 06 (Mon) 15:00

Locate : EB5. 533

Presenter : Jinse Kwon

 

Title : MOSAIC: Heterogeneity-, Communication-, and Constraint-Aware Model Slicing and Execution for Accurate and Efficient Inference

Author : Myeonggyun Han ; Jihoon Hyun ; Seongbeom Park ; Jinsu Park ; Woongki Baek

(UNIST, Republic of Korea)

 

Abstract : Heterogeneous embedded systems have surfaced as a promising solution for accurate and efficient deep-learning inference on mobile devices. Despite extensive prior works, it still remains unexplored to investigate the system-software support that efficiently executes inference workloads by judiciously considering their performance and energy heterogeneity, communication overheads, and constraints. To bridge this gap, we propose MOSAIC, heterogeneity-, communication-, and constraint-aware model slicing and execution for accurate and efficient inference on heterogeneous embedded systems. MOSAIC generates the efficient model slicing and execution plan for the target inference workload through dynamic programming. MOSAIC significantly reduces inference latency and energy, exhibits high estimation accuracy, and incurs small overheads.

Full Paper : IEEE

Article source: //eslab.cnu.ac.kr/en/Mobile/173-MOSAIC-Heterogeneity-Communication-and-Constraint-Aware-Model-Slicing-and-Execution.html

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