pVM: persistent virtual memory for efficient capacity scaling and object storage

Abstract

Next-generation byte-addressable nonvolatile memories (NVMs), such as phase change memory (PCM) and Memristors, promise fast data storage, and more importantly, address DRAM scalability issues. State-of-the-art OS mechanisms for NVMs have focused on improving the block-based virtual file system (VFS) to manage both persistence and the memory capacity scaling needs of applications. However, using the VFS for capacity scaling has several limitations, such as the lack of automatic memory capacity scaling across DRAM and NVM, inefficient use of the processor cache and TLB, and high page access costs. These limitations reduce application performance and also impact applications that use NVM for persistent object storage with flat namespaces, such as photo stores, NoSQL databases, and others. To address such limitations, we propose persistent virtual memory (pVM), a system software abstraction that provides applications with (1) automatic OS-level memory capacity scaling, (2) flexible memory placement policies across NVM, and (3) fast object storage. pVM extends the OS virtual memory (VM) instead of building on the VFS and abstracts NVM as a NUMA node with support for NVM-based memory placement mechanisms. pVM inherits benefits from the cache and TLB-efficient VM subsystem and augments these further by distinguishing between persistent and nonpersistent capacity use of NVM. Additionally, pVM achieves fast persistent storage by further extending the VM subsystem with consistent and durable OS-level persistent metadata. Our evaluation of pVM with memory capacity-intensive applications shows a 2.5x speedup and up to 80% lower TLB and cache misses compared to VFS-based systems. pVM's object store provides 2x higher throughput compared to the block-based approach of the state-of-the art solution and up to a 4x reduction in the time spent in the OS.