Implicit Memory Tagging: No-Overhead Memory Safety Using Alias-Free Tagged ECC


연구 분야: Verification



학회: ISCA '23: Proceedings of the 50th Annual International Symposium on Computer Architecture


초록

Memory safety is a major security concern for unsafe programming languages, including C/C++ and CUDA/OpenACC. Hardware-accelerated memory tagging is an effective mechanism for detecting memory safety violations; however, its adoption is challenged by significant meta-data storage and memory traffic overheads. This paper proposes Implicit Memory Tagging (IMT), a novel approach that provides no-overhead hardware-accelerated memory tagging by leveraging the system error correcting code (ECC) to check for the equivalence of a memory tag in addition to its regular duties of detecting and correcting data errors. Implicit Memory Tagging relies on a new class of ECC codes called Alias-Free Tagged ECC (AFT-ECC) that can unambiguously identify tag mismatches in the absence of data errors, while maintaining the efficacy of ECC when data errors are present. When applied to GPUs, IMT addresses the increasing importance of GPU memory safety and the costs of adding meta-data to GPU memory. Ultimately, IMT detects memory safety violations without meta-data storage or memory access overheads. In practice, IMT can provide larger tag sizes than existing industry memory tagging implementations, enhancing security.


Author Profile
Michael B Sullivan

NVIDIA Austin TX USA

United States
Author Profile
Mohamed Tarek Ziad

NVIDIA Westford MA USA

Morocco
Author Profile
Aamer Jaleel

NVIDIA Westford MA USA

Morocco

📄 논문 정보

발행 연도 2023년
인용수 10
출판 국가 Morocco, United States
사이트 ACM
좋아요 수 0

연관 논문 목록 (229건)