Residue codes have been traditionally used for compute error correction rather than storage error correction. In this paper, we use these codes for storage error correction with surprising results. We find that adapting residue codes to modern memory systems offers a level of error correction comparable to traditional schemes such as Reed-Solomon with fewer bits of storage. For instance, our adaptation of residue code – MUSE ECC – can offer ChipKill protection using approximately 30% fewer bits. We show that the storage gains can be used to hold metadata needed for emerging security functionality such as memory tagging or to provide better detection capabilities against Rowhammer attacks. Our evaluation shows that memory tagging in a MUSE-enabled system shows a 12% reduction in memory bandwidth utilization while providing the same level of error correction as a traditional ECC baseline without a noticeable loss of performance. Thus, our work demonstrates a new, flexible primitive for co-designing reliability with security and performance.

Memory safety continues to be a significant software reliability and security problem, and low overhead and low complexity hardware solutions have eluded computer designers. In this paper, we explore a pathway to deployable memory safety defenses. Our technique builds on a recent trend in software: the usage of binning memory allocators. We observe that if memory allocation sizes (e.g., malloc sizes) are made an architectural feature, then it is possible to overcome many of the thorny issues with traditional approaches to memory safety such as compatibility with unsecured software and significant performance degradation. We show that our architecture, No-FAT, incurs an overhead of 8% on SPEC CPU2017 benchmarks, and our VLSI measurements show low power and area overheads. Finally, as No-FAT’s hardware is aware of the memory allocation sizes, it effectively mitigates certain speculative attacks (e.g., Spectre-V1) with no additional cost. When our solution is used for pre-deployment fuzz testing it can improve fuzz testing bandwidth by an order of magnitude compared to state-of-the-art approaches.