Swapping only occurs if your RAM is full. Most install guides suggest deactivating swap altogether these days.
When working with heavy node tasks, a high cpu clock speed is important, because node doesn't really do multithreading. More cores come into play when working with docker.
Your GPU is mostly not being hit. Apart from training AI models, development isn't gpu-intensive.
The most important piece of hardware for me is a fast SSD. That actually speeds up the times needed for file operations - which is 90% of what I do day to day.
So yeah, your virtualbox hits hard on your CPU, but you're fine with everything else.
I disagree. RAM makes a big difference in a virtualized OS (especially Win10 in Virtualbox - easily testable by increasing allocated guest RAM).
You can gain performance at the cost of some features being harder to configure (shared folders, clipboard, though both can still be accomplished) by using KVM (Kernel Virtual Machine, one of my favorite Linux features) instead of VBox, as it is closer to bare metal.
When working with heavy node tasks, a high cpu clock speed is important, because node doesn't really do multithreading. More cores come into play when working with docker.
Yes, I also use Node.js and Docker.
Thanks for explanation, though.
I don't yet know much about AI models, but I am currently learning about Decision Tree Analysis, Clustering, and Association Mining. But indeed, I heard about GPU requirements from Deep Learning, on YouTube.
I also tempted to try DaVinci Resolve (VDO editing).
For further actions, you may consider blocking this person and/or reporting abuse
We're a place where coders share, stay up-to-date and grow their careers.
Swapping only occurs if your RAM is full. Most install guides suggest deactivating swap altogether these days.
When working with heavy node tasks, a high cpu clock speed is important, because node doesn't really do multithreading. More cores come into play when working with docker.
Your GPU is mostly not being hit. Apart from training AI models, development isn't gpu-intensive.
The most important piece of hardware for me is a fast SSD. That actually speeds up the times needed for file operations - which is 90% of what I do day to day.
So yeah, your virtualbox hits hard on your CPU, but you're fine with everything else.
I disagree. RAM makes a big difference in a virtualized OS (especially Win10 in Virtualbox - easily testable by increasing allocated guest RAM).
You can gain performance at the cost of some features being harder to configure (shared folders, clipboard, though both can still be accomplished) by using KVM (Kernel Virtual Machine, one of my favorite Linux features) instead of VBox, as it is closer to bare metal.
I normally allocate 4GB to Windows on VirtualBox, on another MacAir (around 2018, I think).
And when running PowerBI, it still lags.
Yes, I also use Node.js and Docker.
Thanks for explanation, though.
I don't yet know much about AI models, but I am currently learning about Decision Tree Analysis, Clustering, and Association Mining. But indeed, I heard about GPU requirements from Deep Learning, on YouTube.
I also tempted to try DaVinci Resolve (VDO editing).