Energy Efficient Cluster Usage: Difference between revisions
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carefully about how many resources your jobs |
carefully about how many resources your jobs |
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really need and whether your application really |
really need and whether your application really |
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benefits from allocating more cores for the jobs. |
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Application speedup is often limited and does not |
Application speedup is often limited and does not |
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scale linearly with the number of dedicated cores. But |
scale linearly with the number of dedicated cores. But |
Revision as of 17:38, 26 October 2022
General Issue with Energy Efficiency
You are all aware of the rising energy costs and you are certainly careful to economize your energy consumption at home. But are you aware that computing power also consumes energy? An average compute job running on just a single node for one day can easily consume 10 kWh or even more.
That translates roughly to one of the following activities:
- toasting about 1330 slices of toast in a toaster
- continuously blow-drying your hair for about 10 hours
- actively working on a laptop for about 500 hours
- brewing 700 cups of coffee
Besides energy costs, even this single job alone will also contribute to climate change by adding around 5 kg of CO 2 to the atmosphere which is roughly equivalent to driving a distance of 30 km by car.
You get the point: Please always keep this in mind when submitting tens or even hundreds of jobs to the queue, just like you do when switching on your electrical devices at home. Also, please always think carefully about how many resources your jobs really need and whether your application really benefits from allocating more cores for the jobs. Application speedup is often limited and does not scale linearly with the number of dedicated cores. But energy consumption usually does ...
Using as many resources as possible does not make a power user. Using them wisely does. If in doubt, just ask.