Synergy: Towards On-Body AI via Tiny AI Accelerator Collaboration on Wearables

The advent of tiny artificial intelligence (AI) accelerators enables AI to run at the extreme edge, offering reduced latency, lower power cost, and improved privacy. When integrated into wearable devices, these accelerators open exciting opportunities, allowing various AI apps to run directly on the body. We present Synergy that provides AI apps with besteffort performance via system-driven holistic collaboration over AI accelerator-equipped wearables. To achieve this, Synergy provides device-agnostic programming interfaces to AI apps, giving the system visibility and controllability over the app's resource use. Then, Synergy maximizes the inference throughput of concurrent AI models by creating various execution plans for each app considering AI accelerator availability and intelligently selecting the best set of execution plans. Synergy further improves throughput by leveraging parallelization opportunities over multiple computation units. Our evaluations with 7 baselines and 8 models demonstrate that, on average, Synergy achieves a 23.0× improvement in throughput, while reducing latency by 73.9% and power consumption by 15.8%, compared to the baselines

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Publication Details

Journal
IEEE Transactions on Mobile Computing
Published
2025-04-29
DOI
https://doi.org/10.1109/tmc.2025.3564314
Citations
2
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
1.24
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article

Synergy: Towards On-Body AI via Tiny AI Accelerator Collaboration on Wearables

Utku Günay Acer, Fahim Kawsar, Taesik Gong, Chulhong Min et al.
2 citations
IEEE Transactions on Mobile Computing
Digital Transformation in Industry
1.24
article

Synergy: Towards On-Body AI via Tiny AI Accelerator Collaboration on Wearables

Utku Günay Acer, Fahim Kawsar, Taesik Gong, Chulhong Min, Si Young Jang
article en
2 citations

Abstract

The advent of tiny artificial intelligence (AI) accelerators enables AI to run at the extreme edge, offering reduced latency, lower power cost, and improved privacy. When integrated into wearable devices, these accelerators open exciting opportunities, allowing various AI apps to run directly on the body. We present Synergy that provides AI apps with besteffort performance via system-driven holistic collaboration over AI accelerator-equipped wearables. To achieve this, Synergy provides device-agnostic programming interfaces to AI apps, giving the system visibility and controllability over the app's resource use. Then, Synergy maximizes the inference throughput of concurrent AI models by creating various execution plans for each app considering AI accelerator availability and intelligently selecting the best set of execution plans. Synergy further improves throughput by leveraging parallelization opportunities over multiple computation units. Our evaluations with 7 baselines and 8 models demonstrate that, on average, Synergy achieves a 23.0× improvement in throughput, while reducing latency by 73.9% and power consumption by 15.8%, compared to the baselines

IEEE Transactions on Mobile ComputingVol. 24(10)
Ulsan National Institute of Science and Technology (KR), Nokia (United States) (US)
Openalex Percentile: Top 20%
Digital Transformation in Industry
1.24
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