uMMAP-IO: User-Level Memory-Mapped I/O for HPC
Sergio Rivas-Gomez, Alessandro Fanfarillo, Sebastien Valat, Christophe Laferriere, Philippe Couvée, Sai Narasimhamurthy, Stefano Markidis · 2019
The integration of local storage technologies alongside traditional parallel file systems on HPC clusters, is expected to rise the programming complexity on scientific applications aiming to take advantage of the increased-level of heterogeneity. In this work, we present uMMAP-IO, a user-level memory-mapped I/O implementation that simplifies data management on multi-tier storage subsystems. Compared to the memory-mapped I/O mechanism of the OS, our approach features per-allocation configurable settings (e.g., segment size) and transparently enables access to a diverse range of memory and storage technologies, such as the burst buffer I/O accelerators. Preliminary results indicate that uMMAP-IO provides at least 5-10x better performance on representative workloads in comparison with the standard memory-mapped I/O of the OS, and approximately 20-50% degradation on average compared to using conventional memory allocations without storage support up to 8192 processes.