Hi Qiuye,

somehow the one-million-dollar/"budget vs. program specs vs. current/future applications//vs. access to central computing facilities/" question, is it not?

As Paul indicated, for a personal/office graphics workstation (maximally 128GB ram memory), a 8-16 core CPU with a passmark <https://www.cpubenchmark.net/high_end_cpus.html> of >27.500 and for <600 US$ will do (intel i9-12900, i7-12700, i5-12600k; Ryzen 5950x, 5900x or 5800x). As heat dissipation is a major problem, AMD is a good choice for the moment (i9-12900k TDP 241 watts vs. 3950x TDP 105 watts). If there is a reasonable chance, the system is to be upgraded in the future to a small/medium 2x GPU CryoSpark workstation, plan for a 16-core CPU from the beginning and make sure to choose a motherboard that offers the possibility of 2x PCIe 4.0 at *8x/8x* speed mode (MSI MPG Z690 FORCE / Gygabyte X570*S* Aorus PRO) as many standard boards only offer 16x/4x speed mode (read the technical description carefully; most if not all boards <300 US$ offer 16x/4x only).

As for the graphics card, it depends mainly on program specs, structure-model-size / e.d.-map-size and screen resolution.

For a 4K screen in combination with rendering, you will indeed require a >4000 cuda-cores GPU card such as a 8GB RTX3060ti (600 €; 4864 cuda-cores; 200 watt and sadly no FE model available) or a 16GB RTX A4000 (1100 €; 6144 cuda-cores; 140 watt). Again, as heat dissipation is a major problem, the A4000 is a very good pick with 16GB memory! I recommend a professional RTX *A*xx00-series over the wide-spread 3x00-series consumer cards (*FE* models if at all!) as for the moment, Nvidia still allows the installation of the CUDA-package (AlphaFold, etc., etc.) on consumer cards outside of any central university computing facility without restrictions (read the small print in the cuda software documention), but I would not be surprized this might change in the future (recall the LHR measures taken by the company)! Nvidia can tell from the IP-adress who-is-who (office, home or central computing facility).

For a 1440p screen and small- to mid-sized models/maps, an A2000 (3328 cuda-cores, 30% more cores than a 2070 super; 650-750€; 70 watt) with 6 or 12GB GDDR is good although not a bargain compared to the A4000 that offers a much better price/performance ratio.

Paul's dream-machine - an 3990X combined with a Nvidia RTX 3090 Ti - will cost you, build-it-yourself, at least 8.000 €, which is just too expensive in my eyes.....

A build-it-yourself machine around a Ryzen 5800x, 12GB RTX A2000, 2TB M.2, 12TB HDD and 32GB ram including power-supply and case will cost about 2600 €, and with a Ryzen 5950x and 16GB RTX A4000 about 3100 €.

A minimal system for about 1100€ can be build around a Ryzen 5600x or intel i5-12500 (passmark > 20.000), 16Gb ram and a 6GB GTX 1660 super (1408 cuda-cores; max. 1440p resolution; we run AlphaFold v2 on such a card, not superfast but it gets the job done), for smaller models/maps of course and with slower Coot1 fancy mode I guess ....

It all boiles down to budget in the end I guess, good luck at taking the right decision!


Am 15.04.22 um 17:32 schrieb Qiuye Li:
Dear all,
We recently centralized our high-end workstations and no longer have easy access to their displays, and thus need a modeling computer. I found coot 0.9/wincoot 0.9 are a bit laggy on our less frequently updated office computers, and the all-new coot 1 probably requires even more hardware resources? With this recent launch of coot 1, it is probably a good time to kindly ask for hardware suggestions, like CPU, RAM, SSD, and dGPU. With coot, I typically visualize a .mrc map using a radius of ~25 A and work with real-space refinement/other simple manual adjustments. Other than coot, I often have  1-2 active chimera/Phenix windows open, a few SSH tunnels, and some web pages. I'll be happy to provide more details if needed. Any suggestions are appreciated!



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