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Reducing Carbon footprint of Computing Systems

Project Coordinator (EU) :

Chalmers University of Technology

Country of the EU Coordinator :

Sweden

Project participants :

EU: Chalmers University of Technology

Ahmed Ali-Eldin Hassan  is a PhD. researcher, and is leading an effort into cloud efficiency, and energy-efficient edge computing.  He has been working on the power-performance tradeoffs of computing systems including on debloating machine learning (ML) systems. The research interests aim to reduce the resource consumption of cloud and ML systems by limiting the power allocated to an application and removing unnecessary features and inefficiencies in cloud and ML systems using automated tools.

 

US: University of Massachusetts, Amherst:

 

Dr. Shenoy and his colleagues have been funded by the NSF to design a "Carbon First" approach to (i) make carbon a first-class systems design goal and (ii) to decarbonize cloud computing through carbon-aware software optimizations. These two projects address complementary issues and will come together to experiment with making cloud software applications energy-efficient and zero-carbon.

State of US partner :

Massachusetts

Starting date :

Reducing Carbon footprint of Computing Systems


Experiment description

As noted earlier, the exponential growth of cloud platforms and the resulting growth in energy usage will become unsustainable due to the high carbon cost of cloud workloads. The community has realized the need to ensure new research to ensure sustainable growth of cloud platforms. For example, research has shown that training a single large machine learning model can result in as much carbon emissions as those emitted by a car for an entire year.

Our hypothesis is that there are significant opportunities for making modern cloud application (such as ML training and others) carbon- aware, and employing carbon-aware software design that incorporates such opportunities is necessary to making cloud computing sustainable. Our systems and experimental research will demonstrate these issues through its emphasis on greening cloud computing.

The proposed research and experiment are as follows. First, we will consider several applications such as ML training, distributed "big-data" data-processing, and web-microservices to quantify their power-performance trade-offs. By studying the power, we will also learn about their energy and carbon footprint. The carbon footprint of an application depends on the carbon footprint of the electricity/energy supply, which varies by region and by country.

Our experiment will use NSF CloudLab sites in the US and the edge lab from AI Sweden in Sweden, along with different public EU cloud providers. We will run the same workload at different sites to measure energy and carbon usage and show how carbon usage can vary by region and over time. After performing this baseline experiment, we will consider how to reduce the carbon usage of cloud applications, potentially making them zero carbon. This
will be achieved through multiple techniques. We will leverage our work (at Chalmers) on software debloating of large applications such as ML training to remove bloat which leads to resource waste. Further, we will use workload elasticity techniques (being studied at UMass) to dynamically adapt the carbon consumption of the debloated applications based on the carbon intensity.

For example, the resource usage can be elastically increased when the proportion of renewable energy in the supplied electricity is high. A service such as
Electricity Map which exposes the carbon cost of energy in various parts of US and EU will be used to obtain the carbon data (we already have a collaboration with the Electricity Map service). We will then experimentally run these green versions of our applications on CloudLab and SICS North datacenter and demonstrate the reduction in carbon usage by these applications. The research will yield design principles for making cloud platforms and
applications sustainable and low carbon.

Impacts :

Impact 1: Enhanced EU – US cooperation in Next Generation Internet, including policy cooperation.

  • The project will host many US top researchers in ApPLIED along with many of their EU counterparts. In addition, at least four EU researchers will be hosted by UMass.
  • The project's focus is on carbon-neutral computing. We believe that our results can be used by policy makers to enhance the discussions on how the NGI, 6G, and other systems can be built to be carbon-neutral.

Impact 3: Developing interoperable solutions and joint demonstrators, contributions to standards.
Our end goal is to build a joint demonstrator, with much better integration between our testbeds.

Impact 4: An EU - US ecosystem of top researchers, hi-tech start-ups / SMEs and Internet-related communities collaborating on the evolution of the Internet
We will host a panel in ApPLIED to discuss these topics, including how the evolution of the Internet, and of distributed systems in general will be over the coming decade.

 

Results :

The project's focus is on carbon-neutral computing. We believe that our results can be used by policy makers to enhance the discussions on how the NGI, 6G, and other systems can be built to be carbon-neutral.

NGI related Topic :

Greening the Internet

Call Reference :

4

The 30-months project NGIatlantic.eu will push the Next Generation Internet a step further by providing cascade funding to EU-based researchers and innovators in carrying out Next Generation Internet related experiments in collaboration with US research teams.




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