) is a recently developed post-CMOS FET, which offers intriguing characteristics for high-speed and low-power design in both logic and memory applications. In this article, we present
, a non-volatile cache memory design based on
) memory bit-cell with separate read and write paths. We show that with proper co-design across MEFET device, memory cell circuit, and array architecture, MeF-RAM is a promising candidate for fast
). To evaluate its cache performance in the memory system, we, for the first time, build a device-to-architecture cross-layer evaluation framework to quantitatively analyze and benchmark the MeF-RAM design with other memory technologies, including both volatile memory (i.e., SRAM, eDRAM) and other popular non-volatile emerging memory (i.e., ReRAM, STT-MRAM, and SOT-MRAM). The experiment results for the PARSEC benchmark suite indicate that, as an L2 cache memory, MeF-RAM reduces
Energy Area Latency
) product on average by ~98% and ~70% compared with typical 6T-SRAM and 2T1R SOT-MRAM counterparts, respectively.
Data security is an indispensable part of non-volatile memory (NVM) systems. However, implementing data security efficiently on NVM is challenging, since we have to guarantee the consistency of user data and the related security metadata. Existing consistency schemes ignore the recoverability of the SGX style integrity tree (SIT) and the access correlation between metadata blocks, thereby generating unnecessary NVM write traffic. In this article, we propose SecNVM, an efficient and write-friendly metadata crash consistency scheme for secure NVM. SecNVM utilizes the observation that for a lazily updated SIT, the lost tree nodes after a crash can be recovered by the corresponding child nodes in NVM. It reduces the SIT persistency overhead through a restrained write-back metadata cache and exploits the SIT inter-layer dependency for recovery. Next, leveraging the strong access correlation between the counter and DMAC, SecNVM improves the efficiency of security metadata access through a novel collaborative counter-DMAC scheme. In addition, it adopts a lightweight address tracker to reduce the cost of address tracking for fast recovery. Experiments show that compared to the state-of-the-art schemes, SecNVM improves the performance and decreases write traffic a lot, and achieves an acceptable recovery time.
Existing semantic formalisations of the Intel-x86 architecture cover only a small fragment of its available features that are relevant for the
semantics of multi-threaded programs as well as the
semantics of programs interfacing with non-volatile memory.
We extend these formalisations to cover: (1) non-temporal writes, which provide higher performance and are used to ensure that updates are flushed to memory; (2) reads and writes to other Intel-x86 memory types, namely uncacheable, write-combined, and write-through; as well as (3) the interaction between these features. We develop our formal model in both operational and declarative styles, and prove that the two characterisations are equivalent. We have empirically validated our formalisation of the consistency semantics of these additional features and their subtle interactions by extensive testing on different Intel-x86 implementations.
AbstractAlthough SRAM is a well-established type of volatile memory, data remanence has been observed at low temperature even for a power-off state, and thus it is vulnerable to a physical cold boot attack. To address this, an ultra-fast data sanitization method within 5 ns is demonstrated with physics-based simulations for avoidance of the cold boot attack to SRAM. Back-bias, which can control device parameters of CMOS, such as threshold voltage and leakage current, was utilized for the ultra-fast data sanitization. It is applicable to temporary erasing with data recoverability against a low-level attack as well as permanent erasing with data irrecoverability against a high-level attack.
Welcome to this installment of the ACM SIGMOD Record's series of interviews with distinguished members of the database community. I'm Marianne Winslett, and today I have here with me Joy Arulraj, who won the 2019 ACM SIGMOD Jim Gray Dissertation Award for his thesis entitled The Design and Implementation of Non-volatile Memory Database Management Systems. Joy is now an Assistant Professor at Georgia Tech, and his PhD is from the Carnegie Mellon University, where he worked with Andy Pavlo, who won this same award in his time. So, Joy, welcome!