I do use CUDA, though not on my laptop. My usual workflow has been to fiddle around with the code on a minimal dataset which takes up most of my time. Once I'm happy with the logic and how things work, the heavy crunching (if required) is offloaded to CUDA workstations/servers.
The thing that gives me the most pause is how fractured the academic bioinformatics software scene is, and how poorly they're maintained once published. I've often run across requirements for GCC beyond what's included in the current Ubuntu LTS, for example. In my old lab I kept a CUDA workstation running the latest Manjaro for these eventualities, among others.
edit: I think one of the most important and convenient things is to get a NAS or build a small fileserver. That way you can decouple most of your personal stuff from the systems you are using via NFS/SMB/CIFS and give a damn about interoperability of filesystems, thereby gaining the ability to try out what works best for you without much hassle.