Posted by
Olaf Selchow on
URL: http://confocal-microscopy-list.275.s1.nabble.com/Lightsheet-imaging-analysis-Workstation-Specs-tp7590391p7590406.html
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Hello everybody,
Happy to share a bit of my experience on this:
- Re the multiview deconvolution by Preibisch et al - with GPU enhancement: It works but my experience also is that it could be a bit easier to get the installation done. CUDA support is not depreciated though, to my knowledge.
- Typical data set size in what I have done in Light Sheet Microscopy in recent years is 500 GB to 10 TB both, in live imaging (long timer series with multiple views) and imaging of optically cleared specimen.
- Re the specs of a suitable machine, the following things I would consider (depends on how many people will use it, how many microscopes connected, installation location of the processing computer)
1. With Imaris and / or arivis vision4D to be run on the same machine as Fiji and maybe the manufacturers software (Zeiss ZEN, Leica LAS X, 3i Slidebook, etc) you want to run Windows, I guess.
2. If you want to be able to use it with multiple users in parallel you want/need Windows Server.
3. I would make sure that the microscopes are connected with direct 10 Gbit. Over an institutional network, even if 10 Gbit, you might be limited in bandwidth and so you can migrate the data only after acquisition from the acquisition PC to the Storage. This costs time, blocks the acquisition PC and essentially duplicates the required storage capacity you need. I always try to bring the microscopes with the processing & analysis computers in a 10 Gbit subnet that I can manage with a dedicated router/firewall/switch. That prevents interferences with all the other traffic in your institute.
4. I would not use a NAS. Processing data by loading data into memory / software via network (and saving the results / temp data via the same line) can take ages. 10 Gbit is far too slow in my view. I’d use a prcessing machine with a strong RAID controler and a large RAID array directly attached to the processing unit. And I would save the data from the microscopes directly to this volume.
5. if you need super large RAM depends on how many people are supposed to work in parallel on this machine, if you want to use VMs, and what software you use (arivis needs much less RAM than others. Fiji benefits a lot from super large RAM, etc.). But if you choose the right motherboard and OS, you can always and easily upgrade RAM later.
6. CPU: generally, large multicore CPUs speed up things. But some software, even today, doesn’t make much use of parallelization. If you buy a very expensive dual-44-core CPU for thousands of $/€ you might end up with the software not using it. Actual check out the workflows. Some vendors might say „yes, our software uses all cores available“ , but in the end the processing function you are using most might still be running on a single or only 2 cores.
7. Monitor: I have worked with a number of 32 inch UHD 4K (3840 x 2160, 16:9) and 32 inch WQHD 3.6K (2560 x 1440, 16:9) monitors and never had a real problem. But thi smight depend on the GPU you use.
8. GPUs:
- if you want to use 3D renderings over remote access (e.g., RDP) sessions, I strongly recommend professional GPUs. I know, they are expensive. But the drivers on the Geforce or other gaming-grade GPUs can give you a hard time when working remotely. I have good experience with NVIDIA Quadro RTX boards (they are, in some GPU CUDA processing tasks, 2x faster than the previous P-seroes that is otherwise also perfectly fine.) For 3D viewing / rendering / analyzing data, make sure the VRAM on the GPU is 11 GB / 16 GB or larger.
- for some software and for VMs, it makes sense to think of the option of multiple GPUs. Maybe you just want to make sure you can fit a 2nd or 3rd later on. In SVI Huygens you can, for example, assign instances of DCV to certain GPUs - so multiple GPUs can speed up your work. You need to buy the respective licenses from SVI though.
9. Storage volume: make sure you have multiple (2 or more) fast volumes (RAIDs of HDD or SSDs) to have space for the software where it can save temp data - on an independent volume. Multiple simultaneous read/write processes can slow down even fast RAID configs. Also keep in mind that SSDs are more convenient and faster, but still more expensive and still have a higher failure rate. Mak sure you consider hard drives 7 ssds as consumables. In a RAID of 15 HDDs, it is perfectly normal that you have 1 HDD/year in average that fails and needs replacement. SSDs maybe even more often.
The Lenovo Think Station P920 is certainly a great hardware. You’ll still have to invest a bit of time and money to get it ready to work for your applications. Networking i, etc.
I would also point out that there is commercial options that provide you a turnkey solution with support that can scale / grow with your needs.
I have worked with ACQUIFER HIVEs a lot. Check with them or a similar provider if your budget allows a high end solution for 60k (+) $/€ and if you are looking for a solution provider that saves you from configuring network adapters yourself …
Note: I used to have consultancy projects with ACQUIFER and might have more in the future. So I am a bit biased, but mostly because I think they have great hardware and services and I worked wit them to position their products and improve them. I do not (!) have a direct financial interest in them selling a platform unit to you!
I hope this helps.
best regards,
Olaf
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Dr. Olaf Selchow
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Microscopy & BioImaging Consulting
Image Processing & Large Data Handling
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[hidden email]