Abstract
As clouds increase in size and as machines of different types are added to the infrastructure in order to maximize performance and power efficiency, heterogeneous clouds are being created. However, exploiting different architectures poses significant challenges. To efficiently access heterogeneous resources and, at the same time, to exploit these resources to reduce application development effort, to make optimisations easier and to simplify service deployment, requires a re-evaluation of our approach to service delivery. We propose a novel cloud management and delivery architecture based on the principles of self-organisation and self-management that shifts the deployment and optimisation effort from the consumer to the software stack running on the cloud infrastructure. Our goal is to address inefficient use of resources and consequently to deliver savings to the cloud provider and consumer in terms of reduced power consumption and improved service delivery, with hyperscale systems particularly in mind. The framework is general but also endeavours to enable cloud services for high performance computing. Infrastructure-as-a-Service provision is the primary use case, however, we posit that genomics, oil and gas exploration, and ray tracing are three downstream use cases that will benefit from the proposed architecture.
Original language | English |
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Title of host publication | CLOSER 2016 - Proceedings of the 6th International Conference on Cloud Computing and Services Science |
Publisher | SciTePress |
Pages | 333-338 |
Number of pages | 6 |
Volume | 1 |
ISBN (Electronic) | 9789897581823 |
Publication status | Published - 1 Jan 2016 |
Externally published | Yes |
Event | 6th International Conference on Cloud Computing and Services Science, CLOSER 2016 - Rome, Italy Duration: 23 Apr 2016 → 25 Apr 2016 |
Conference
Conference | 6th International Conference on Cloud Computing and Services Science, CLOSER 2016 |
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Country/Territory | Italy |
City | Rome |
Period | 23/04/16 → 25/04/16 |
Keywords
- Cloud Architecture
- Cloud Computing
- Cloud Computing Models
- Cloud Infrastructures
- Cloud Orchestration
- Cloud Services Self-organisation
- Data Flow Engine
- DFE
- FPGA
- GPU
- Heterogeneous Resources
- Many-integrated Cores
- MIC
- Resource as a Service
- Self-management