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One mistake you already described is using virtualization. Nothing is more reliable than running your code directly on your hardware, without intermediaries (even when the virtualization software and Windows are evolving each day). It will be better to have a dual-boot system if you really need Windows than virtualization. To avoid mistakes, you need to ...


18

"Are there critical mistakes to avoid when creating a matter modeling workstation (32-128 cores)?" 32-128 is quite a big range since at 128 you'd be limited to non-mainstream chips like the Ampere and as far as I know, the most cores in an Intel processor apart from the Xeon Phi line (which was discontinued in 2020 and wasn't a conventional ...


18

As previously stated, arguably the most mature and widely used set of tools is currently a combination of Pymatgen, FireWorks, Custodian, and Atomate (which is built upon the prior three Python packages). These tools were constructed as part of the Materials Project but have seen uses in other high-throughput DFT studies. Another general workflow package for ...


15

Several computational workflow managers try to address exactly this problem in materials modeling. Besides helping orchestrating complex simulation workflows, they keep track of all the simulations (and how they are related) in a database. The Materials Project team uses the Fireworks package. The atomate package provides a high-level interface for the most ...


15

I think these are some of the most popular: pymatgen(+fireworks+custodian --> atomate) these are all part of materials project, there are some good references available OpenQD this is a database like materials project but it's been used for high-throughput calculations AiiDA seems relatively newer but the site has a ton of good documentation and ...


12

I would suggest to stay away from niche solutions and start with one mainstream machine. The most direct reason is that you get much more computing power for the same money if you buy mass-produced hardware. A more indirect reason is that everything you buy next year will be 20% cheaper or faster, your choice, cumulative for each year. If you want optimal ...


11

QMCPACK: is a modern high-performance open-source Quantum Monte Carlo (QMC) simulation code. QMCPACK is closely related to Nexus, which is another High Throughput Computing package for Quantum Chemistry calculations. To add on to something Andrew Rosen said "There are also many field-specific packages that attempt to automate workflows specific to ...


10

[Disclaimer - I am one of the co-authors of the 2D database on Materials Cloud (What you call "2D structures and layered materials", publishing the data of this work: N. Mounet et al., Nature Nanotech. 13, 246–252 (2018) so I will mostly refer to it below] In general, these studies "extract" a layer from a bulk 3D material, and then often ...


10

The answer by Kevin Jablonka is much more specific to matter modeling, but I wanted to point out that the screenshot example from Medea-VASP shown in the question, can be imitated almost exactly with most general schedulers (not specific to VASP) such as SLURM, PBS, LoadLeveler, Oracle Engine Grid, etc. The squeue command in SLURM will give output very ...


9

To invest in new hardware, just to have it crippled by Intel MKL afterwards. This was object of a question I asked here previously. In matter modeling, it's usual for people to compile software themselves, instead of relying in precompiled binaries, so it can be tuned to the particular processor model in their machine, for example, taking advantage of more ...


9

Buying an Intel CPU would be one, for sure. (unless you are buying an Ice Lake server) I think the biggest decision to make is to build a CPU box or a GPU box. For atom-centered Gaussian basis set quantum chemistry you probably going to want a CPU box, with lots of RAM and a very fast and a high endurance SSD.


6

One critical mistake is to invest heavily in GPUs before doing a cost/benefit analysis. A single GPU may cost $2000, which can already get you 2-3 good compute nodes. Many codes (e.g. https://gaussian.com/g16/gpus.pdf) advertise speedups that are underwhelming: the GPU speedup should be at least an order of magnitude, when the CPU code is already close to ...


6

The community-edited awesome materials informatics list has a section on "software frameworks", which includes many of the tools mentioned in the answers here & more. Contributions welcome!


3

QCArchive The MolSSI QCArchive project is designed for running, storing and accessing hundreds of millions of quantum chemistry calculations for individuals and groups of researchers at any scale. The project has been discussed in a recent article, WIREs e1491 (2020), which also has a chemRxiv preprint.


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