Energy Efficient Algorithms

May 12, 2020 | White Papers

May 2020

In this Ekkono SWP (Short White Paper) we discuss the fact and use of Energy Efficient Algorithms. While more and more devices are being connected, they consume more and more energy. What happens when you also run machine learning (ML) on these devices? How can we design ML models that are as environmentally friendly as possible from the start? And better how can we design algorithms that also train devices to be better and smarter and therefore minimize their CO2 footprint?

At Ekkono we have a sustainable mindset from start to finish. We focus on making our ML algorithms as energy efficient as possible, to make sure our set of algorithms and software library does not consume more energy than necessary. In this SWP we also explain the benefits of energy efficient machine learning algorithms, such as less processing power, fewer CPU cycles, and less memory consuming.

Click the image to download the SWP document (pdf).

Ekkono’s SWP are documented results of our #openfika webinars.

The webinars are also recorded and available to watch in our YouTube channel or below:

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