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I forecast 400k timeseries every 30minutes at work.

What kind of infrastructure do you use for that scale? Are these computationally light ARIMA models?

We're running 150k models per day and while I'm sure I could scale this to running them every 30 minutes, it would mostly be me throwing money at the problem to parallelize the compute.

Some HPC Clusters, xgboost, read pretrained model from NFSRDMA Server, read data, parallelise over MPI with one process per model. And the latest Zen5 Epycs. I could do it all on just one of the 192 cores EPYCs but we like to parallelise it over multiple machines to get the extra speed and reliablity.

It wasn't that expensive, the main problem was the storage bottleneck which got fixed with just some LVM cache and gen5 ssds.

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