Scalable High-Performance QoS
Large-scale, high-performance storage systems are gaining momentum in data centers and high performance computing systems. Quality of Service (QoS) will be an essential feature as storage systems scale out in capacity and number of clients to support because QoS can help ensuring high resource utilization and fair resource allocation between competing clients. Few existing QoS solutions are designed to work at the scale that can support millions of concurrent client accesses. This research project aims at designing scalable QoS solutions for these large-scale, high-performance storage systems.
The current focus of this project is Automating Contention Management for High-Performance Storage Systems, see the Ascar project page for more information.
|Nov 13, 2017||
Ethan L. Miller,
Darrell D. E. Long,
CAPES: Unsupervised Storage Performance Tuning Using Neural Network-Based Deep Reinforcement Learning,Supercomputing '17, November 2017. [Scalable High-Performance QoS] [Tracing and Benchmarking] [Ultra-Large Scale Storage]
|Jun 2, 2015||Yan Li, Xiaoyuan Lu, Ethan L. Miller, Darrell D. E. Long, Scalable High-Performance QoS] [Ultra-Large Scale Storage] [Storage QoS]|
|Jan 1, 2000||Jehan-François Pâris, Steven W. Carter, Darrell D. E. Long, Scalable High-Performance QoS]|
Last modified 23 Apr 2015