NVStream
Pradeep Fernando, Ada Gavrilovska, Sudarsun Kannan, Greg Eisenhauer · 2018
Nonvolatile memory technologies (NVRAM) with larger capacity relative to DRAM and faster persistence relative to block-based storage technologies are expected to play a crucial role in accelerating I/O performance for HPC scientific workflows. Typically, a scientific workflow includes a simulation process (producer of data) and an analytics application process (consumer of data) that stream, share, and exchange data supported by an underlying OS-level file system. However, using an OS-level file system for data sharing adds substantial software overheads due to frequent system calls, journaling (for crash-consistency) cost, and file-system metadata update cost. To overcome these challenges, we design NVStream- a lightweight user-level data management system that exploits NVRAMs byte addressability and fast persistence to support streaming I/O in scientific workflows. First, NVStream reduces I/O-related software overheads by designing a memory-based persistent object store and log-structured heap manager that exploit NVRAM's large capacity. Second, NVStream incorporates a hardware-assisted non-temporal stores for crash-consistent updates at near hardware data copy (memory copy) speeds. Finally, NVStream reduces data written to NVRAM with a delta compression, which further reduces I/O cost for workflows with higher write locality. The evaluation of NVStream using I/O benchmarks and scientific applications demonstrates 10X reduction in I/O compared to NVRAM-optimized file systems and also guaranteeing crash-consistent data movement.