Optimized Memory Tagging on AmpereOne Processors

TL;DR

This paper presents an optimized implementation of Memory Tagging Extension (MTE) on AmpereOne datacenter processors, achieving low overhead and high security for memory safety in cloud workloads.

Contribution

It introduces a hardware-efficient MTE implementation on AmpereOne that incurs no memory overhead and offers minimal performance impact, along with analysis of software optimization opportunities.

Findings

No memory capacity overhead for tag storage.

Single-digit performance impact across workloads.

Hardware-software stack analysis reveals software as a key overhead source.

Abstract

Memory-safety escapes continue to form the launching pad for a wide range of security attacks, especially for the substantial base of deployed software that is coded in pointer-based languages such as C/C++. Although compiler and Instruction Set Architecture (ISA) extensions have been introduced to address elements of this issue, the overhead and/or comprehensive applicability have limited broad production deployment. The Memory Tagging Extension (MTE) to the ARM AArch64 Instruction Set Architecture is a valuable tool to address memory-safety escapes; when used in synchronous tag-checking mode, MTE provides deterministic detection and prevention of sequential buffer overflow attacks, and probabilistic detection and prevention of exploits resulting from temporal use-after-free pointer programming bugs. The AmpereOne processor, launched in 2024, is the first datacenter processor to support MTE. Its optimized MTE implementation uniquely incurs no memory capacity overhead for tag storage and provides synchronous tag-checking with single-digit performance impact across a broad range of datacenter class workloads. Furthermore, this paper analyzes the complete hardware-software stack, identifying application memory management as the primary remaining source of overhead and highlighting clear opportunities for software optimization. The combination of an efficient hardware foundation and a clear path for software improvement makes the MTE implementation of the AmpereOne processor highly attractive for deployment in production cloud environments.