Energy Efficiency: An Emerging Architectural Concern Rabih Bashroush Dublin, 13 June 2014

Outline Background & overview Drivers for change Open challenges Predicting the future!

Background and Overview IT activity has entered a new era – “By the end of 2011, 20 typical households would generate more traffic than the entire Internet in 2008”, [Cisco, 2010] – By 2015, >2,500% mobile data [NSN, 2011] – data-growth of 4,400% [IDC, 2012]

Background and Overview More than 50% of all new applications are anticipated to be cloud based within the next 2 years More than 50% of all applications are anticipated to be cloud based within the next 4 years) In 5-10 years, >90% of all applications in the cloud [GlassHouse]

Background and Overview IT systems consume 6% of the UK’s national power grid It is predicted that the Internet would consume all of Japan’s energy production by 2030 GHG Emissions from data centres is expected to quadruple by 2020 overtaking the carbon emissions of the entire aviation industry.

Infrastructure needs energy… Time magazine reported that it takes kWh to stream 1 minute of video from the YouTube data centre… Based on Jay Walker’s recent TED talk, 0.01kWh of energy is consumed on average in downloading 1MB over the Internet. The average Internet device energy consumption is around 0.001kWh for 1 minute of video streaming For 1.7B downloads of this 17MB file and streaming for 4 minutes gives the overall energy for this one pop video in one year…

312GWh from 15 th July 2012… 36MW of 24/7/365 diesel generation 100 million Litres fuel oil 250,000 Tons CO2 80,000 average UK car-years 312GWh = more than the annual electricity consumption of Burundi, population 9 million (273GWh in 2008)

Drivers for Change Energy costs are the fastest-rising cost element in the data centre (30-60% of TCO) Europe – Europe 2020 and the Digital Agenda (20% increase in E/E) – New Legislations and CoC – Research Direction (Horizon 2020) UK – Government inserting CoC into ICT RFQs – The Eight Great Technologies – New procurement policy for server (liaising with EU & Energy Star) USA is slower, energy is cheaper and low demand on ‘green’ solutions

Drivers for Change Publications by Year

Drivers for Change Publications by Country

200 W idle Server +5.4 W Power Distribution W UPS W Cooling W Switchgear/Tr ansformer = W Wasted Energy

Open Challenges Varying workloads (peak times, spikes,...) and operating environment Predicting the shape of the workload of the future Lack of the ability to communicate across the different layers (s/w, platform, h/w, network, cooling, environment, etc.) to enable cross-layer optimization

Open Challenges Lack of formal methods to capture and represent energy consumption, reliability, user experience, etc. to enable tradeoff analysis Lack of benchmarks to allow realistic comparisons of different approaches Disjoint research communities

Open Challenges How to make applications energy aware by design – Modeling energy constraints at architecture level – Understanding energy cost of design decisions

Predicting the future Allocate workloads to servers based on the cooling profile of the data centre Set the performance of an application based on budget requirements Match application types to most efficient hardware types and ambient conditions Match application requirements in real-time to run in optimal energy cost (e.g. time of day, or based on real-time energy price)

Top500 June 2013, China PetaFLOPS c20,000x 1997 Source: But predicting the future of IT is risky – the world’s fastest super-computer SANDIA National Laboratories ‘ASCI RED’ 1.8 teraflops 150m² raised floor 800kW +9 years 2006 Sony Playstation3 1.8 teraflops 0.08m² <0.2kW