CERN's Exabyte Data Center
blog.westerndigital.com
blog.westerndigital.com
An Exabyte of disk is definitely eyebrow-raising, but companies like LinkedIn had an exabyte of storage in 2021 just in their HDFS clusters.
https://www.linkedin.com/blog/engineering/open-source/the-ex...
Isn't it a bit harsh to lose 1.7% of data every year? Why not a dead simple RAID that can tolerate the loss of a disk without data loss?
Their datacenter is used for a lot more than just LHC results, also. Zenodo, the open science result repository, also lives in their storage.
Is there ever a point where they can safely delete this data? Or do they have to keep it forever?
The last time I had to buy disks I switched to Seagate Exos X and thought I'll continue buying them. I think it was one of the Backblaze Drive Stats which made me buy them. I like the drives.
So CERN is now doing again such an advertising campaign:
> When Bonfillou shared the requirements from the next generation collider, the team suggested testing the company’s new series of JBODs (Just a Bunch of Drives), the Ultrastar hybrid storage platforms.
Since the project is expected to start in 2029, add about at least 5 more years for CERN to collect data on the drive stats, that's a long time to wait.
Does anyone here know if WD's Ultrastar are still as good as back then, when HGST was HGST? Was it just a brand change and all the rest, R&D-team, design, production, was still the same, separate to WD?
[0] https://rog.asus.com/articles/news/hgst-ships-6tb-ultrastar-...
[1] https://www.westerndigital.com/en-us/products/internal-drive...
Nvidia itself was basically bankrolled by DoE labs for much of it's early existence, MPI was a HPC project driven by Oak Ridge, the WWW was a side project at CERN to simplify information retrieval, etc.
High Energy Physics is a very data and computationally heavy problem that lends itself nicely to HPC, and a lot of the innovations in CS subfields like Bioinformatics, Machine Learning, and Theory was enabled by this research.
> 'How's the spacecraft doing?' 'I dunno. All this equipment is just used to measure TV ratings.'
There's very sophisticated compression systems throughout each experiment's data acquisition pipelines. For example this paper[1] describes the ALICE experiment's system for Run3, involving FPGAs and GPUs to be able to handle 3.5TB/s from all the detectors. This one [2] outlines how HL-LHC & CMS use neural networks to fine tune compression algorithms on a per-detector basis.
Not to mention your standard data files are ROOT TFiles with TTrees which store arrays of compressed objects.
It's all pretty neat.
The article has a sub-headline:
> A petabyte per second
The math doesn't work out for me, unless there at 30 ALICE equivalents at CERN. I think there are about 3.