ARM MTE Performance in Practice
Taehyun Noh, Yingchen Wang, Tal Garfinkel, Mahesh Madhav, Daniel Moghimi, Mattan Erez, Shravan Narayan
摘要
We present the first comprehensive analysis of ARM MTE hardware performance on four different microarchitectures: ARM Big (A7x), Little (A5x), and Performance (Cortex-X) cores on the Google Pixel 8 and Pixel 9, and on Ampere Computing's AmpereOne CPU core. We also include preliminary analysis of MTE on Apple's M5 chip. We investigate performance in MTE's primary application—probabilistic memory safety—on both SPEC CPU benchmarks and in server workloads such as RocksDB, Nginx, PostgreSQL, and Memcached. While MTE often exhibits modest overheads, we also see performance slowdowns up to 6.64× on certain benchmarks. We identify the microarchitectural cause of these overheads and where they can be addressed in future processors. We then analyze MTE's performance for more specialized security applications such as memory tracing, time-of-check time-of-use prevention, sandboxing, and CFI. In some of these cases, MTE offers significant advantages today, while the benefits for other cases are negligible or will depend on future hardware. Finally, we explore where prior work characterizing MTE performance has either been incomplete or incorrect due to methodological or experimental errors.
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引用它的顶会 Paper2
- PoisonCap: Efficient Hierarchical Temporal Safety for CHERIYuecheng Wang, Jonathan Woodruff, Alfredo Mazzinghi, Peter Rugg 等CCS 2026 · 被引用 3 次
- NanoTag: Systems Support for Efficient Byte-Granular Overflow Detection on ARM MTEMingkai Li, Hang Ye, Joseph Devietti, Suman Jana 等S&P 2026 · 被引用 1 次
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- You shall not (by)pass!: practical, secure, and fast PKU-based sandboxingAlexios Voulimeneas, Jonas Vinck, Ruben Mechelinck, Stijn VolckaertEuroSys 2022 · 被引用 33 次
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