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MICRO2023顶会

Accelerating Extra Dimensional Page Walks for Confidential Computing

Dong Du, Bicheng Yang, Yubin Xia, Haibo Chen

2023年份
7被引次数
2顶会引用

摘要

To support highly scalable and fine-grained computing paradigms such as microservices and serverless computing better, modern hardware-assisted confidential computing systems, such as Intel TDX and ARM CCA, introduce permission table to achieve finegrained and scalable memory isolation among different domains. However, it also adds an extra dimension to page walks besides page tables, leading to significantly more memory references (e.g., 4 12 for RISC-V Sv39) 1 . We observe that most costs (about 75%) caused by the extra dimension of page walks are used to validate page table pages. Based on this observation, this paper proposes HPMP (Hybrid Physical Memory Protection), a hardware-software co-design (on RISC-V) that protects page table pages using segment registers and normal pages using permission tables to balance scalability and performance. We have implemented HPMP and Penglai-HPMP (a TEE system based on HPMP) on FPGA with two RISC-V cores (both in-order and out-of-order). Evaluation results show that HPMP can reduce costs by 23.1%-73.1% on BOOM and significantly improve performance on real-world applications, including serverless computing (FunctionBench) and Redis. 1 All memory reference numbers presented in this paper adhere to the RISC-V ISA specification [105] and do not take into account PWC or other micro-architecture optimizations that could potentially bypass page table pages.

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