> For example, I use Solidworks, so I need to run windows.
Right. One of the things a lot of people don't get is the extent to which multidisciplinary workflows require Windows. This is particularly true of web-centric software engineers who simply do not have any exposure to the rest of the engineering universe.
Years ago this was the reason we had to drop using Raspberry Pi's little embedded microcontroller. The company is Linux-centric to such an extent that they simply could not comprehend how telling someone "Just switch to Linux" is in a range between impossible and nonsensical. They were, effectively, asking people to upend their PLM process just for the sake of using a little $0.50 part. You would have to do things like store entire OS images and configurations just to be able to reconstruct and maintain a design iteration from a few years ago.
WSL2 is pretty good. We still haven't fully integrated this into PLM workflows though. That said, what we've done on our machines was to install a separate SSD for WSL2. With that in place, backing-up and maintaining Linux distributions or distributions created in support of a project is much, much easier. This, effectively, in some ways, isolates WSL2 distributions from Windows. I can clone that drive and move it from a Windows 10 machine to a Windows 11 machine and life is good.
For AI workflows with NVIDIA GPU's WSL2 is less than ideal. I don't know if things have changed in this domain since I last looked. Our conclusion from a while back was that, if you have to do AI with the usual toolchains, you need to be on a machine running Linux natively rather than a VM running under Windows. It would be fantastic if this changed and one could run AI workflows on WSL2 without CUDA and other issues. Like I said, I have not checked in probably a year, maybe things are better now?
EDIT: The other reality is that one can have a nice powerful Linux machine next to the Windows box and simply SSH into it to work. Most good IDE's these days support remote development as well. If you are doing something serious, this is probably the best setup. This is what we do.
Right. One of the things a lot of people don't get is the extent to which multidisciplinary workflows require Windows. This is particularly true of web-centric software engineers who simply do not have any exposure to the rest of the engineering universe.
Years ago this was the reason we had to drop using Raspberry Pi's little embedded microcontroller. The company is Linux-centric to such an extent that they simply could not comprehend how telling someone "Just switch to Linux" is in a range between impossible and nonsensical. They were, effectively, asking people to upend their PLM process just for the sake of using a little $0.50 part. You would have to do things like store entire OS images and configurations just to be able to reconstruct and maintain a design iteration from a few years ago.
WSL2 is pretty good. We still haven't fully integrated this into PLM workflows though. That said, what we've done on our machines was to install a separate SSD for WSL2. With that in place, backing-up and maintaining Linux distributions or distributions created in support of a project is much, much easier. This, effectively, in some ways, isolates WSL2 distributions from Windows. I can clone that drive and move it from a Windows 10 machine to a Windows 11 machine and life is good.
For AI workflows with NVIDIA GPU's WSL2 is less than ideal. I don't know if things have changed in this domain since I last looked. Our conclusion from a while back was that, if you have to do AI with the usual toolchains, you need to be on a machine running Linux natively rather than a VM running under Windows. It would be fantastic if this changed and one could run AI workflows on WSL2 without CUDA and other issues. Like I said, I have not checked in probably a year, maybe things are better now?
EDIT: The other reality is that one can have a nice powerful Linux machine next to the Windows box and simply SSH into it to work. Most good IDE's these days support remote development as well. If you are doing something serious, this is probably the best setup. This is what we do.