Composable architecture for rack scale big data computing

Li, Chung-Sheng; Franke, Hubertus; Parris, Colin; Abali, Bülent; Kesavan, Mukil; Chang, Victor

doi:10.1016/j.future.2016.07.014

Cited by 51 publications

(27 citation statements)

References 34 publications

(48 reference statements)

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“…[6] evaluates the impact of data-centric workloads on the design of DC. Their observation suggests heterogeneity in the DC, in which running a job on the most cost-efficient server reduces the overall cost.…”

Section: Related Workmentioning

confidence: 99%

Techno-economic framework for cloud infrastructure: a cost study of resource disaggregation

Mahloo

Soares

Roozbeh

2017

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

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Abstract-The rapid growth of data and high-dependency of industries on using data put lots of focus on the computing facilities. Increasing the efficiency and re-architecting the underlying infrastructure of datacenters, has become a major priority. The total cost of owning and running a datacenter (DC) is affected by many parameters, which until recently were ignored as their impact on the business economy was negligible. However, that is not the case anymore, as in the new era of digital economy every penny counts. The market is too aggressive to ignore anything. Hence, the economic efficiency becomes vital for cloud infrastructure providers despite their size. This article presents a framework to assess cloud infrastructure economic efficiency, taking into account three main aspects: application profiling, hardware dimensioning and total cost of ownership (TCO). Moreover, it presents a cost study of deploying the emerging concept of disaggregated hardware architecture in DCs based on the proposed framework. The study considers all the major cost categories incurred during the DC lifetime in terms of both capital and operational expenditures. A thorough cost comparison between a DC running on a disaggregated hardware architecture with one running on a traditional server-based hardware architecture is presented. The study demonstrates the evolution of the yearly cost over DC lifetime as well as a sensitivity analysis, allowing to understand how to minimize the cost of running cloud. Results show that, lifecycle management cost is one of the main differentiators between two technologies. Moreover, it is shown that in the presence of heterogeneous workloads, having a DC based on a fully disaggregated hardware brings high savings (more than 40% depending on the applications) compared to the traditional hardware architectures independent of the hardware set-up.Index Terms-datacenter cost, disaggregated hardware, total cost of ownership, hardware pools, reconfigurable hardware

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Section: Related Workmentioning

confidence: 99%

Techno-economic framework for cloud infrastructure: a cost study of resource disaggregation

Mahloo

Soares

Roozbeh

2017

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

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“…With this technology, the cost of hardware maintenance and acquisition can be reduced and, as a consequence, the service delivery cost can also be reduced. According to Reference , this design approach “ offers the potential advantage of enabling continuous peak workload performance while minimizing resource fragmentation for fast evolving heterogeneous workloads .”…”

Section: Introductionmentioning

confidence: 99%

Availability analysis of design configurations to compose virtual performance‐optimized data center systems in next‐generation cloud data centers

et al. 2020

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Next-generation cloud data centers are based on software-defined data center infrastructures that promote flexibility, automation, optimization, and scalability. The Redfish standard and the Intel Rack Scale Design technology enable software-defined infrastructure and disaggregate bare-metal compute, storage, and networking resources into virtual pools to dynamically compose resources and create virtual performance-optimized data centers (vPODs) tailored to workload-specific demands. This article proposes four chassis design configurations based on Distributed Management Task Force's Redfish industry standard applied to compose vPOD systems, namely, a fully shared design, partially shared homogeneous design, partially shared heterogeneous design, and not shared design; their main difference is based on the used hardware disaggregation level. Furthermore, we propose models that combine reliability block diagram and stochastic Petri net modeling approaches to represent the complexity of the relationship between the pool of disaggregated hardware resources and their power and cooling sources in a vPOD. These four proposed design configurations were analyzed and compared in terms of availability and component's sensitivity indexes by scaling their configurations considering different data center infrastructure. From the obtained results, we can state that, in general, when one increases the hardware disaggregation, availability is improved. However, after a given point, the availability level of the fully shared, partially shared homogeneous, and partially shared heterogeneous configurations remain almost equal, while the not shared configuration is still able to improve its availability. K E Y W O R D Savailability, composable systems, next-generation cloud data center, Redfish standard, stochastic models Softw: Pract Exper. 2020;50:805-826.wileyonlinelibrary.com/journal/spe

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“…Resource disaggregation can be implemented physically or logically at different scales i.e. rack-scale, pod-scale or DC-scale [27]. The composition of logical hosts from disaggregated resources adopts virtualization technologies and other software-oriented techniques to abstract the control plane of physical resources from their data plane and for control, orchestration and monitoring.…”

Section: Introductionmentioning

confidence: 99%

A Network Topology for Composable Infrastructures

Ajibola

El-Gorashi

Elmirghani

2020

2020 22nd International Conference on Transparent Optical Networks (ICTON)

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This paper proposes a passive optical backplane as a new network topology for composable computing infrastructures. The topology provides a high capacity, low-latency and flexible fabric that interconnects disaggregated resource components. The network topology is dedicated to inter-resource communication between composed logical hosts to ensure effective performance. We formulated a mixed integer linear programming (MILP) model that dynamically creates logical networks to support intra logical host communication over the physical network topology. The MILP performs energy efficient logical network instantiation given each application's resource demand. The topology can achieve 1Tbps capacity per resource node given appropriate wavelength transmission data rate and the right number of wavelengths per node.

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Composable architecture for rack scale big data computing

Cited by 51 publications

References 34 publications

Techno-economic framework for cloud infrastructure: a cost study of resource disaggregation

Techno-economic framework for cloud infrastructure: a cost study of resource disaggregation

Availability analysis of design configurations to compose virtual performance‐optimized data center systems in next‐generation cloud data centers

A Network Topology for Composable Infrastructures

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