I’m new, but am hoping to start a masters program in addition to doing work for my own business applications. I’m interested in augmented reality, natural language processing, and simulations.
I don’t have any of these components yet. For the first 2-3 years I don’t expect to have more than 2x GPUs unless there’s a strong business need - in which case I could also utilize cloud offerings.
Between these two builds, which would you choose? The threadripper with it’s future compatability for 4x GPUs, or the ryzen with it’s low cost and support for 2x GPUs? The cost is equal between the two.
I had been using Tim Dettmers guides mainly when selecting my builds. In the guides, he says the RTX 2070 is the best to start with, and to get twice as much RAM as your video card supports (rounding up to get 32).
The 2080 Ti had seemed more than I would need, but I’m curious why we have two people so far are suggesting 64gb ram and the 2080 Ti over the 2070 super? It’s a deviation from the guides and my proposed builds that I wasn’t expecting
Also, the single GPU suggestion is surprising. A part of me thinks it could be good experience and fun to learn to parallelize across GPUs, but another part of me is happy to hear that a single gpu is enough for my needs because of the cost savings.
64GB RAM: Because pandas uses exponentially more memory in larger dataframes.
I could easily, easily use 128GB/256GB on a 4GB sqlite db
Actually I’ll also respond regarding the Super; they’re a crappy branded card for gamers. Anyone who does anything with the card, like video editing or ML is going to want 11gb of vram. Just get a 2070 instead of a super and save $$ if you’re going the cheap route.