The University of Southampton
University of Southampton Institutional Repository

Composable architecture for rack scale big data computing

Composable architecture for rack scale big data computing
Composable architecture for rack scale big data computing
The rapid growth of cloud computing, both in terms of the spectrum and volume of cloud workloads, necessitate re-visiting the traditional rack-mountable servers based datacenter design. Next generation datacenters need to offer enhanced support for: (i) fast changing system configuration requirements due to workload constraints, (ii) timely adoption of emerging hardware technologies, and (iii) maximal sharing of systems and subsystems in order to lower costs. Disaggregated datacenters, constructed as a collection of individual resources such as CPU, memory, disks etc., and composed into workload execution units on demand, are an interesting new trend that can address the above challenges. In this paper, we demonstrated the feasibility of composable systems through building a rack scale composable system prototype using PCIe switch. Through empirical approaches, we develop assessment of the opportunities and challenges for leveraging the composable architecture for rack scale cloud datacenters with a focus on big data and NoSQL workloads. In particular, we compare and contrast the programming models that can be used to access the composable resources, and developed the implications for the network and resource provisioning and management for rack scale architecture.
big data platforms, composable system architecture, disaggregated datacenter architecture, composable datacenter, software defined environments, software defined networking
180-193
Li, Chung-Sheng
d8201cde-ec26-4ae8-b686-e4eee1291bf9
Franke, Hubertus
2808a2d3-e1ad-407f-a871-4758446c226d
Parris, Colin
bb5d9334-2b5f-4df8-8115-d51dec62441c
Abali, Bulent
8a8a4ef5-f123-4343-99c8-270abfea2de3
Kesavan, Mukil
e17854b9-a220-41f1-a08f-dc8cd9803b55
Chang, Victor
a7c75287-b649-4a63-a26c-6af6f26525a4
Li, Chung-Sheng
d8201cde-ec26-4ae8-b686-e4eee1291bf9
Franke, Hubertus
2808a2d3-e1ad-407f-a871-4758446c226d
Parris, Colin
bb5d9334-2b5f-4df8-8115-d51dec62441c
Abali, Bulent
8a8a4ef5-f123-4343-99c8-270abfea2de3
Kesavan, Mukil
e17854b9-a220-41f1-a08f-dc8cd9803b55
Chang, Victor
a7c75287-b649-4a63-a26c-6af6f26525a4

Li, Chung-Sheng, Franke, Hubertus, Parris, Colin, Abali, Bulent, Kesavan, Mukil and Chang, Victor (2017) Composable architecture for rack scale big data computing. Future Generation Computer Systems, 67, 180-193. (doi:10.1016/j.future.2016.07.014).

Record type: Article

Abstract

The rapid growth of cloud computing, both in terms of the spectrum and volume of cloud workloads, necessitate re-visiting the traditional rack-mountable servers based datacenter design. Next generation datacenters need to offer enhanced support for: (i) fast changing system configuration requirements due to workload constraints, (ii) timely adoption of emerging hardware technologies, and (iii) maximal sharing of systems and subsystems in order to lower costs. Disaggregated datacenters, constructed as a collection of individual resources such as CPU, memory, disks etc., and composed into workload execution units on demand, are an interesting new trend that can address the above challenges. In this paper, we demonstrated the feasibility of composable systems through building a rack scale composable system prototype using PCIe switch. Through empirical approaches, we develop assessment of the opportunities and challenges for leveraging the composable architecture for rack scale cloud datacenters with a focus on big data and NoSQL workloads. In particular, we compare and contrast the programming models that can be used to access the composable resources, and developed the implications for the network and resource provisioning and management for rack scale architecture.

Text
FGCS_Disaggregated_Datacenter_accepted.pdf - Accepted Manuscript
Download (977kB)

More information

Accepted/In Press date: 19 July 2016
Published date: 1 February 2017
Keywords: big data platforms, composable system architecture, disaggregated datacenter architecture, composable datacenter, software defined environments, software defined networking
Organisations: Electronic & Software Systems

Identifiers

Local EPrints ID: 398349
URI: http://eprints.soton.ac.uk/id/eprint/398349
PURE UUID: 6152989b-ec24-4a8b-bf1a-fdaebc5eea40

Catalogue record

Date deposited: 21 Jul 2016 16:37
Last modified: 15 Mar 2024 05:45

Export record

Altmetrics

Contributors

Author: Chung-Sheng Li
Author: Hubertus Franke
Author: Colin Parris
Author: Bulent Abali
Author: Mukil Kesavan
Author: Victor Chang

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×