SoftVN: efficient memory protection via software-provided version numbers
SoftVN: efficient memory protection via software-provided version numbers
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DOI：
10.1145/3470496.3527378
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发表时间：
2022-06
期刊：
影响因子：
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通讯作者：
M. Umar;Weizhe Hua;Zhiru Zhang;G. Suh
中科院分区：
文献类型：
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作者：
M. Umar;Weizhe Hua;Zhiru Zhang;G. Suh
处理器中的可信执行环境（TEE）保护片外存储器（DRAM），并使用存储器加密和完整性验证来确保其机密性和完整性。然而，这样的存储器保护可能招致显著的性能开销，因为它需要针对诸如版本号（VN）和MAC之类的保护元数据的附加存储器访问。本文提出了SoftVN，扩展到当前的内存保护方案，它显着降低了开销，今天的国家的最先进的允许软件提供VN的内存访问。对于具有用于大数据结构的简单存储器访问模式的存储器密集型应用，仅需要针对数据结构而不是单独的高速缓存块来维护VN，并且可以在软件中以低工作量来跟踪VN。如果软件跟踪并提供用于内存读取的片外VN访问，则可以删除它们。我们通过模拟各种内存密集型应用程序来评估SoftVN，包括深度学习，图形处理和生物信息学算法。实验结果表明，SoftVN与类似于Intel SGX的基线相比，内存保护开销减少了82%，性能平均提高了33%。最大性能提升可高达65%。
Trusted execution environments (TEEs) in processors protect off-chip memory (DRAM), and ensure its confidentiality and integrity using memory encryption and integrity verification. However, such memory protection can incur significant performance overhead as it requires additional memory accesses for protection metadata such as version numbers (VNs) and MACs. This paper proposes SoftVN, an extension to the current memory protection schemes, which significantly reduces the overhead of today's state-of-the-art by allowing software to provide VNs for memory accesses. For memory-intensive applications with simple memory access patterns for large data structures, the VNs only need to be maintained for data structures instead of individual cache blocks and can be tracked in software with low efforts. Off-chip VN accesses for memory reads can be removed if they are tracked and provided by software. We evaluate SoftVN by simulating a diverse set of memory-intensive applications, including deep learning, graph processing, and bioinformatics algorithms. The experimental results show that SoftVN reduces the memory protection overhead by 82% compared to the baseline similar to Intel SGX, and improves the performance by 33% on average. The maximum performance improvement can be as high as 65%.