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UMap: Enabling Application-driven Optimizations for Page Management by Peng, Ivy B.; McFadden, Marty; Green, Eric; Iwabuchi, Keita; Wu, Kai; Li, Dong; Pearce, Roger; Gokhale, Maya is a scholarly article available to read on EtoBox.

What is UMap: Enabling Application-driven Optimizations for Page Management about?

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 us

Author

Peng, Ivy B.; McFadden, Marty; Green, Eric; Iwabuchi, Keita; Wu, Kai; Li, Dong; Pearce, Roger; Gokhale, Maya

Published

2019

Language

EN