Dear readers, this summer has flown by, and now it is time to tie up any loose ends. As the countdown continues, my colleague and I are hard at work wrapping everything up.

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When at first my supervisor told me that he wanted no job run times to be under-predicted, the task seemed daunting, almost impossible. How could I make sure that my algorithm never erred in such a way? In this post I explain how I tackled this problem and how the classical accuracy metric can be misleading and even futile in certain machine learning environments.

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Well that’s an odd question… you just file up in a queue obviously, or the shortest queue if there are multiple ones, and get in the back of such line. Well yes, that is one way to do it, and …

So, what’s the right way to get in line? Read More »

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Hey there, I’m Francesca and I am one of the lucky participants of the PRACE summer of HPC, edition 2020. I did my bachelor studies in Applied Mathematics and after working for a few years I decided I wanted to …

Francesca Schiavello Read More »

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Project reference: 2015 The broad userbase of clusters is not familiar with the ins-and-outs of the systems they are working on and such familiarity is not really necessary. As a result many will enqueue jobs with maximum available run time …

Machine Learning for the rescheduling of SLURM jobs Read More »

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