25837

Safe and Practical GPU Acceleration in TrustZone

Heejin Park, Felix Xiaozhu Lin
Purdue ECE
arXiv:2111.03065 [cs.DC], (4 Nov 2021)

@misc{park2021safe,

   title={Safe and Practical GPU Acceleration in TrustZone},

   author={Heejin Park and Felix Xiaozhu Lin},

   year={2021},

   eprint={2111.03065},

   archivePrefix={arXiv},

   primaryClass={cs.DC}

}

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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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