DATE: Wednesday, June 22, 2011 - NOTE SPECIAL DAY
TIME: 12:00 pm - 1:00 pm

SPEAKER: Steven Swanson, UC San Diego

TITLE: Moneta: Engineering Storage for the Data Age

Emerging, fast non-volatile memories are around 1000s of times faster than conventional disks in terms of latency, and they offer enormous gains in bandwidth as well. Fully leveraging these technologies will require far-reaching changes in how storage systems operate. To understand the impact of this increased storage performance, we have developed a prototype high-performance storage system called Moneta. Our experience with Moneta shows that system and application software designed for a world of slow disks is a poor fit for storage devices based on these new technologies. Moneta's hardware interface and software stack work together to remove software overheads such as disk-centric IO scheduling, contentious locks, and system call overheads. Moneta also provides a generic facility for removing file system overheads almost entirely. The combination of these optimizations reduces latency for a 4KB read request from 25.5 µs to 7.9 µs and increases sustained bandwidth for small requests by 26 times. We compare Moneta to a range of storage devices based on disks, flash memory, and advanced non-volatile memories, and find that further work is required at the application level to fully leverage the potential of these new memories.

Steven Swanson is an assistant professor in the Department of Computer Science and Engineering at the University of California, San Diego and the director of the Non-volatile Systems Laboratory. His research interests include the systems, architecture, security, and reliability issues surrounding non-volatile, solid-state memories. He also co-leads projects to develop low-power co-processors for irregular applications and to devise software techniques for using multiple processors to speed up single-threaded computations. In previous lives he has worked on scalable dataflow architectures, ubiquitous computing, and simultaneous multithreading. He received his PhD from the University of Washington in 2006.

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