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(Nov 16) Coordinated and Efficient Huge Page Management with Ingens


Coordinated and Efficient Huge Page Management with Ingens


2017.11.16 (Thu) 14:00-


Youngjin Kwon Ph.D. candidate (The University of Texas at Austin)


N1 B/D, #113


Modern computing is hungry for RAM, with today’s enormous capacities eagerly

consumed by diverse workloads. Hardware address translation overheads have

grown with memory capacity, motivating hardware manufacturers to provide TLBs

with thousands of entries for large page sizes (called huge pages). Operating

systems and hypervisors support huge pages with a hodge-podge of best-effort

algorithms and spot fixes that made sense for architectures with limited huge page

support, but the time has come for a more fundamental redesign. Ingens is a

framework for huge page support that relies on a handful of basic primitives

to provide transparent huge page support in a principled, coordinated way.

By managing contiguity as a first-class resource and by tracking utilization

and access frequency of memory pages, Ingens is able to eliminate a number

of fairness and performance pathologies that plague current systems.

Experiments with our prototype demonstrate fairness improvements, performance

improvements (up to 18%), tail-latency reduction (up to 71%), and reduction of

memory bloat from 69% to less than 1% for important applications like Web services

(e.g., the Cloudstone benchmark) and the Redis key-value store.


Youngjin Kwon is a Ph.D. student in The University of Texas at Austin under supervision of

Prof. Emmett Witchel and Prof. Simon Peter. His research interests primarily lie in operating systems,

including file systems, emerging storage and memory technologies, system support for security, and virtualization.