协同作用:通过微型AI加速器在可穿戴设备上的合作实现人体AI

IF 9.2 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Taesik Gong;SiYoung Jang;Utku Günay Acer;Fahim Kawsar;Chulhong Min
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引用次数: 0

摘要

微型人工智能(AI)加速器的出现使AI能够在极端边缘运行,从而减少延迟、降低功耗并改善隐私。当集成到可穿戴设备中时,这些加速器打开了令人兴奋的机会,允许各种人工智能应用程序直接在身体上运行。我们展示了Synergy,通过系统驱动的整体协作,在配备AI加速器的可穿戴设备上为AI应用程序提供最佳性能。为了实现这一点,Synergy为AI应用程序提供了与设备无关的编程接口,使系统对应用程序的资源使用具有可见性和可控性。然后,Synergy考虑AI加速器的可用性,为每个应用程序创建各种执行计划,并智能地选择最佳执行计划集,从而最大限度地提高并发AI模型的推理吞吐量。协同通过利用多个计算单元上的并行化机会进一步提高吞吐量。我们对7个基线和8个模型的评估表明,与基线相比,Synergy平均实现了23.0倍的吞吐量改进,同时将延迟降低了73.9%,功耗降低了15.8%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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 best-effort 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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来源期刊
IEEE Transactions on Mobile Computing
IEEE Transactions on Mobile Computing 工程技术-电信学
CiteScore
12.90
自引率
2.50%
发文量
403
审稿时长
6.6 months
期刊介绍: IEEE Transactions on Mobile Computing addresses key technical issues related to various aspects of mobile computing. This includes (a) architectures, (b) support services, (c) algorithm/protocol design and analysis, (d) mobile environments, (e) mobile communication systems, (f) applications, and (g) emerging technologies. Topics of interest span a wide range, covering aspects like mobile networks and hosts, mobility management, multimedia, operating system support, power management, online and mobile environments, security, scalability, reliability, and emerging technologies such as wearable computers, body area networks, and wireless sensor networks. The journal serves as a comprehensive platform for advancements in mobile computing research.
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