PLDI 2024
Mon 24 - Fri 28 June 2024 Copenhagen, Denmark
Mon 24 Jun 2024 11:10 - 11:25 at Iceland - Optimization Chair(s): Aviral Shrivastava

Image segmentation is one of the major computer vision tasks, which is applicable in a variety of domains, such as autonomous navigation of an unmanned aerial vehicle. However, image segmentation cannot easily materialize on tiny embedded systems because image segmentation models generally have high peak memory usage due to their architectural characteristics. This work finds that image segmentation models unnecessarily require large memory space with an existing tiny machine learning framework. That is, the existing framework cannot effectively manage the memory space for the image segmentation models.

This work proposes TinySeg, a new model optimizing framework that enables memory-efficient image segmentation for tiny embedded systems. TinySeg analyzes the lifetimes of tensors in the target model and identifies long-living tensors. Then, TinySeg optimizes the memory usage of the target model mainly with two methods: (i) tensor spilling into local or remote storage and (ii) fused fetching of spilled tensors. This work implements TinySeg on top of the existing tiny machine learning framework and demonstrates that TinySeg can reduce the peak memory usage of an image segmentation model by 39.3% for tiny embedded systems.

Mon 24 Jun

Displayed time zone: Windhoek change

10:40 - 12:20
OptimizationLCTES at Iceland
Chair(s): Aviral Shrivastava Arizona State University
10:40
15m
Talk
Accelerating Shared Library Execution in a DBT
LCTES
Tom Spink University of St Andrews, Björn Franke University of Edinburgh
10:55
15m
Talk
Efficient Implementation of Neural Networks Usual Layers on Fixed-Point Architectures
LCTES
Dorra Ben Khalifa University of Toulouse - ENAC, Matthieu Martel Université de Perpignan Via Domitia
11:10
15m
Talk
TinySeg: Model Optimizing Framework for Image Segmentation on Tiny Embedded Systems
LCTES
Byungchul Chae Kyung Hee University, Jiae Kim Kyung Hee University, Seonyeong Heo Kyung Hee University
11:25
10m
Break
Break - 10 minutes
LCTES

11:35
15m
Talk
MixPert: Optimizing Mixed-Precision Floating-Point Emulation on GPU Integer Tensor Cores
LCTES
Zejia Lin Sun Yat-sen University, Aoyuan Sun Sun Yat-sen University, Xianwei Zhang Sun Yat-sen University, Yutong Lu Sun Yat-sen University
11:50
15m
Talk
Optimistic and Scalable Global Function Merging
LCTES
12:05
15m
Talk
(Invited paper) Language-Based Deployment Optimization for Random Forest
LCTES
Jannik Malcher TU Dortmund University, Daniel Biebert TU Dortmund University, Kuan-Hsun Chen University of Twente, Sebastian Buschjäger TU Dortmund University, Christian Hakert TU Dortmund University, Jian-Jia Chen TU Dortmund University