Projects
Projects: Projects for Investigator |
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| Reference Number | EP/M015823/1 | |
| Title | Distributed Heterogeneous Vertically IntegrateD ENergy Efficient Data centres | |
| Status | Completed | |
| Energy Categories | Energy Efficiency(Residential and commercial) 100%; | |
| Research Types | Basic and strategic applied research 100% | |
| Science and Technology Fields | PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 100% | |
| UKERC Cross Cutting Characterisation | Not Cross-cutting 100% | |
| Principal Investigator |
Dr H Leather No email address given Sch of Informatics University of Edinburgh |
|
| Award Type | Standard | |
| Funding Source | EPSRC | |
| Start Date | 31 December 2014 | |
| End Date | 30 December 2016 | |
| Duration | 24 months | |
| Total Grant Value | £143,137 | |
| Industrial Sectors | Information Technologies | |
| Region | Scotland | |
| Programme | NC : ICT | |
| Investigators | Principal Investigator | Dr H Leather , Sch of Informatics, University of Edinburgh (99.998%) |
| Other Investigator | Dr B Grot , Sch of Informatics, University of Edinburgh (0.001%) Dr S Viglas , Sch of Informatics, University of Edinburgh (0.001%) |
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| Web Site | ||
| Objectives | ||
| Abstract | Our world is in the midst of a "big data" revolution, driven by the ubiquitous ability to gather, analyse, and query datasets of unprecedented variety and size. The sheer storage volume and processing capacity required to manage these datasets has resulted in a transition away from desktop processing and toward warehouse-scale computing inside data centres. State-of-the-art data centres, employed by the likes of Google and Facebook, draw 20-30 MW of power, equivalent to 20,000 homes, with these companies needing many data centres each. The global data centre energy footprint is estimated at around 2% of the world's energy consumption and doubles every five years (33, 34). Contemporary data centres have an average overhead of 90% (32), meaning that they consume up to 1.9 MW to deliver 1 MW of IT support; this is not cost-effective or environmentally sound. If the exponential data growth and processing capacity are to scale in the way that both the public and industry have come to rely upon, we must tackle the data centre energy crisis or face the reality of stagnated progress. With the semiconductor industry's inability to further lower operating voltages in processor and memory chips, the challenge is in developing technologies for large-scale data-centric computation with energy as a first-order design constraint. The DIVIDEND project attacks the data centre energy efficiency bottleneck through vertical integration, specialisation, and cross-layer optimisation. Our vision is to present heterogeneous data centres, combining CPUs, GPUs, and task-specific accelerators, as a unified entity to the application developer and let the runtime optimise the utilisation of the system resources during task execution. DIVIDEND embraces heterogeneity to dramatically lower the energy per task through extensive hardware specialisation while maintaining the ease of programmability of a homogeneous architecture. To lower communication latency and energy, DIVIDEND leverages SoC integration and prefers a lean point-to-point messaging fabric over complex connection-oriented network protocols. DIVIDEND addresses the programmability challenge by adapting and extending the industry-led heterogeneous systems architecture programming language and runtime initiative to account for energy awareness and data movement. DIVIDEND provides for a cross-layer energy optimisation framework via a set of APIs for energy accounting and feedback between hardware, compilation, runtime, and application layers. The DIVIDEND project will usher in a new class of vertically integrated data centres and will take a first stab at resolving the energy crisis by improving the power usage effectiveness of data centres by at least 50% | |
| Publications | (none) |
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| Final Report | (none) |
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| Added to Database | 13/03/15 | |
