GCPersist

Abstract

The emergence of non-volatile memory (NVM) has stimulated broad interests in building efficient and persistent systems and programming models. However, most prior work is built atop an eager persistency model, which mandates applications to persist their data as soon as possible and thus causes considerable overhead. Besides, prior work mainly focuses on native languages and overlooks the interactions with the managed runtime system in a high-level language. Such issues limit the scope of applications on NVM, especially for resilient applications that already have reliable but inefficient recovery mechanisms. This paper proposes GCPersist, an easy-to-use NVM programming framework atop a lazy persistency model to defer the persistency of user data for better performance, with the assistance of the garbage collection (GC) module in the managed runtime. GCPersist further provides differentiated persistency modes to reduce the runtime overhead. We have implemented GCPersist on the HotSpot JVM of OpenJDK and the evaluation results on Intel Optane DC persistent memory devices show that GCPersist performs well with resilient applications (like Spark) by reducing the recovery time by up to 3.26X while introducing only 1--6% runtime overhead during normal execution.