Composable architecture for rack scale big data computing

Chung Sheng Li, Hubertus Franke, Colin Parris, Bulent Abali, Mukil Kesavan, Victor Chang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

49 Citations (Scopus)

Abstract

The rapid growth of cloud computing, both in terms of the spectrum and volume of cloud workloads, necessitates 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 demonstrate the feasibility of composable systems through building a rack scale composable system prototype using PCIe switches. Through empirical approaches, we develop an 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 develop the implications for the network and resource provisioning and management for rack scale architecture.

Original languageEnglish
Pages (from-to)180-193
Number of pages14
JournalFuture Generation Computer Systems
Volume67
DOIs
Publication statusPublished - 1 Feb 2017

Keywords

  • Big data platforms
  • Composable datacenter
  • Composable system architecture
  • Disaggregated datacenter architecture
  • Software defined environments
  • Software defined networking

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