Welcome to the ADMT Publication Server

Stream Query Processing on Emerging Memory Architectures

DocUID: 2015-006 Full Text: PDF

Author: Chelsea Mafrica, John Johnson, Santiago Bock, Thao N. Pham, Bruce R. Childers, Panos K. Chrysanthis, Alexandros Labrinidis

Abstract: Stream query processing is becoming increasingly important as more time-oriented data is produced and analyzed online. Stream processing is typically memory-resident for the fastest processing of ephemeral data. With workload consolidation, processing separate data streams on the same processor may lead to harmful contention between query workloads. This contention may become particularly problematic as new main memory technologies are adopted, such as phase-change memory, that have asymmetric read and write latency. This work presents a preliminary study of performance implications of consolidation and emerging memory on stream query processing. We show that contention in the memory subsystem worsens with a phase- change main memory, suggesting that new stream optimization and hardware approaches will be required to achieve quality of service and quality of data guarantees in future computer servers.

Published In: Proc. of the 4th IEEE Non-Volatile Memory Systems and Applications Symposium

Year Published: 2015

Project: AQSIOS Subject Area: Data Streams

Publication Type: Conference Paper

Sponsor: NSF CBET-1250171

Citation:Text Latex BibTex XML Chelsea Mafrica, John Johnson, Santiago Bock, Thao N. Pham, Bruce R. Childers, Panos K. Chrysanthis, and Alexandros Labrinidis. Stream Query Processing on Emerging Memory Architectures. Proc. of the 4th IEEE Non-Volatile Memory Systems and Applications Symposium. 2015.