Scalable crash consistency for secure persistent memory

Persistent memory (PM) suffers from data security and crash consistency issues due to non-volatility. Counter-mode encryption (CME) and bonsai merkle tree (BMT) have been adopted to ensure data security by using security metadata. The data and its security metadata need to be atomically persisted for correct recovery. To ensure crash consistency, durable transactions have been widely employed. However, the long-time BMT update increases the transaction latency, and the security metadata incur heavy write traffic. This paper presents Secon to ensure SEcurity and crash CONsistency for PM with high performance. Secon leverages a scalable write-through metadata cache to ensure the atomicity of data and its security metadata. To reduce the transaction latency, Secon proposes a transaction-specific epoch persistency model to minimize the ordering constraints. To reduce the amount of PM writes, Secon co-locates counters with log entries and coalesces BMT blocks. Experimental results demonstrate that Secon significantly improves the transaction performance and decreases the write traffic.