Atlas

Abstract

Non-volatile main memory, such as memristors or phase change memory, can revolutionize the way programs persist data. In-memory objects can themselves be persistent without the need for a separate persistent data storage format. However, the challenge is to ensure that such data remains consistent if a failure occurs during execution. In this paper, we present our system, called Atlas, which adds durability semantics to lock-based code, typically allowing us to automatically maintain a globally consistent state even in the presence of failures. We identify failure-atomic sections of code based on existing critical sections and describe a log-based implementation that can be used to recover a consistent state after a failure. We discuss several subtle semantic issues and implementation tradeoffs. We confirm the ability to rapidly flush CPU caches as a core implementation bottleneck and suggest partial solutions. Experimental results confirm the practicality of our approach and provide insight into the overheads of such a system.