UMap: Enabling Application-driven Optimizations for Page Management

• Published in: 2019 IEEE/ACM Workshop on Memory Centric High Performance Computing (MCHPC) pp. 71 - 78
• Main Authors: Peng, Ivy, McFadden, Marty, Green, Eric, Iwabuchi, Keita, Wu, Kai, Li, Dong, Pearce, Roger, Gokhale, Maya
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-11-2019
• Subjects: Kernel; memmap; Memory management; memory mapping; Optimization; page fault; page management; Prefetching; Task analysis; user- space paging; userfaultfd
• DOI: 10.1109/MCHPC49590.2019.00017

Leadership supercomputers feature a diversity of storage, from node-local persistent memory and NVMe SSDs to network-interconnected flash memory and HDD. Memory mapping files on different tiers of storage provides a uniform interface in applications. However, system-wide services like mmap are optimized for generality and lack flexibility for enabling application-specific optimizations. In this work, we present UMap to enable user-space page management that can be easily adapted to access patterns in applications and storage characteristics. UMap uses the userfaultfd mechanism to handle page faults in multi-threaded applications efficiently. By providing a data object abstraction layer, UMap is extensible to support various backing stores. The design of UMap supports dynamic load balancing and I/O decoupling for scalable performance. UMap also uses application hints to improve the selection of caching, prefetching, and eviction policies. We evaluate UMap in five benchmarks and real applications on two systems. Our results show that leveraging application knowledge for page management could substantially improve performance. On average, UMap achieved 1.25 to 2.5 times improvement using the adapted configurations compared to the system service.