Research on the Relationship between APP Size and Installation Time in Intelligent Mobile Devices

Jiang, Chan Jiang; Li, Shaoyong; Huo, Guangcheng; Luo, Lei

doi:10.1109/dsc.2019.00048

Cited by 2 publications

(1 citation statement)

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“…Compared to Naive, OursMDS reduces the delays by up to 95% to 18 seconds (WiFi) and 30 seconds (cellular) on average. We deem these delays as acceptable, as they are comparable to mobile app installation delays reported to be 10 -50 seconds [35].…”

Section: Performancementioning

confidence: 61%

Safe and Practical GPU Acceleration in TrustZone

Park¹,

Lin²

2021

Preprint

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We present a holistic design for GPU-accelerated computation in TrustZone TEE. Without pulling the complex GPU software stack into the TEE, we follow a simple approach: record the CPU/GPU interactions ahead of time, and replay the interactions in the TEE at run time. This paper addresses the approach's key missing piece -the recording environment, which needs both strong security and access to diverse mobile GPUs. To this end, we present a novel architecture called CODY, in which a mobile device (which possesses the GPU hardware) and a trustworthy cloud service (which runs the GPU software) exercise the GPU hardware/software in a collaborative, distributed fashion. To overcome numerous network round trips and long delays, CODY contributes optimizations specific to mobile GPUs: register access deferral, speculation, and metastate-only synchronization. With these optimizations, recording a compute workload takes only tens of seconds, which is up to 95% less than a naive approach; replay incurs 25% lower delays compared to insecure, native execution.

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Section: Performancementioning

confidence: 61%