Paper Info
Title
A limits study of benefits from nanostore-based future data-centric system architectures
Abstract
The adoption of non-volatile memories (NVMs) in system architecture and the growth in data-centric workloads offer exciting opportunities for new designs. In this paper, we examine the potential and limit of designs that move compute in close proximity to NVM-based data stores. To address the challenges in evaluating such system architectures for distributed systems, we develop and validate a new methodology for large-scale data-centric workloads. We then study "nanostores" as an example design that constructs distributed systems from building blocks with 3D-stacked compute and NVM layers on the same chip, replacing both traditional storage and memory with NVM. Our limits study demonstrates significant potential of this approach (3-162X improvement in energy delay product) over 2015 baselines, particularly for IO-intensive workloads. We also discuss and quantify the impact of network bandwidth, software scalability, and power density, and design tradeoffs for future NVM-based data-centric architectures.
Year
DOI
Venue
2012
10.1145/2212908.2212915
Conf. Computing Frontiers
Keywords
Field
DocType
data-centric workloads,large-scale data-centric workloads,nanostore-based future data-centric system,system architecture,io-intensive workloads,limits study,example design,future nvm-based data-centric architecture,nvm-based data store,nvm layer,design tradeoffs,power density,non volatile memory,chip,data center,distributed system
Database-centric architecture,Computer science,Parallel computing,Baseline (configuration management),Real-time computing,Chip,Non-volatile memory,Bandwidth (signal processing),Software,Systems architecture,Scalability
Conference
Citations 
PageRank 
References 
4
0.43
21
Authors
6
Name
Order
Citations
PageRank
Jichuan Chang154726.22
Parthasarathy Ranganathan23316230.61
Trevor Mudge36139659.74
David Roberts4745.35
Mehul A. Shah53547317.66
Kevin Lim672639.98