CRONUS: Fault-isolated, Secure and High-performance Heterogeneous Computing for Trusted Execution Environment
Jianyu Jiang, Ji Qi, Tianxiang Shen, Xusheng Chen, Shixiong Zhao, Sen Wang, Li Chen, Gong Zhang, Xiapu Luo, Heming Cui
Abstract
With the trend of processing a large volume of sensitive data on PaaS services (e.g., DNN training), a TEE architecture that supports general heterogeneous accelerators, enables spatial sharing on one accelerator, and enforces strong isolation across accelerators is highly desirable. However, none of the existing TEE solutions meet all three requirements. In this paper, we propose CRONUS, the first TEE architecture that achieves the three crucial requirements. The key idea of CRONUS is to partition heterogeneous computation into isolated TEE enclaves, where each enclave encapsulates only one kind of computation (e.g., GPU computation), and multiple enclaves can spatially share an accelerator. Then, CRONUS constructs heterogeneous computing using remote procedure calls (RPCs) among enclaves. With CRONUS, each accelerator’s hardware and its software stack are strongly isolated from others’, and each enclave trusts only its own hardware. To tackle the security challenge caused by inter-enclave interactions, we design a new streaming remote procedure call abstraction to enable secure RPCs with high performance. CRONUS is software-based, making it general to diverse accelerators. We implemented CRONUS on ARM TrustZone. Evaluation on diverse workloads with CPUs, GPUs and NPUs shows that, CRONUS achieves less than 7.1% extra computation time compared to native (unprotected) executions.
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Cited by top-tier papers7
- Honeycomb: Secure and Efficient GPU Executions via Static ValidationHaohui Mai, Jiacheng Zhao, Hongren Zheng, Yiyang Zhao et al.OSDI 2023 · 39 citations
- sNPU: Trusted Execution Environments on Integrated NPUsErhu Feng, Dahu Feng, Dong Du, Yubin Xia et al.ISCA 2024 · 13 citations
- Salus: A Practical Trusted Execution Environment for CPU-FPGA Heterogeneous Cloud PlatformsYu Zou, Yiran Li, Sheng Wang, Le Su et al.ASPLOS 2024 · 3 citations
- SoK: Analysis of Accelerator TEE DesignsChenxu Wang, Junjie Huang, Yujun Liang, Xuanyao Peng et al.NDSS 2026 · 2 citations
- TZ-LLM: Protecting On-Device Large Language Models with Arm TrustZoneXunjie Wang, Jiacheng Shi, Zihan Zhao, Yang Yu et al.EuroSys 2026 · 1 citation
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