bought legion 7i: Intel i9 12th gen, rtx 3080 ti 16 gb vram, 32 GB ddr5. need some confirmation bias (or opposite) to understand if I made the right decision

Submitted by macORnvidia t3_ynd8r9 in deeplearning

Please read if I made the right purchase because I'm really not good at spending money on myself. So I want opinions. Haven't even opened the box yet.

Not for gaming and I understand people always say you train your deep learning models on a cluster and I agree.

But I wanted to get into cuda, pycuda, clara, frameworks from nvidia and wanted a new laptop because my generic surface gave up after more than half a decade of improvising.

Plus for basic prototyping in DL, and machine learning code optimization using pycuda, I believed it would be nice to have a local device where I can learn all this without having to move data between clusters and my device.

Macs can't do cuda so they were out. And I didn't want some weird gamey built like asus, razers have bad thermals, Alienware in the same price range has i7 not i9 cpu plus felt plasticky.

Legion 7i looked, felt pretty solid, metal chassis, decent thermals and specs. But open to reconsider within the 15 day period if need be.

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arhetorical t1_iv8fays wrote

You already got the advice not to buy a laptop for deep learning. But if you're determined and understand that it's not a great idea to begin with, then any laptop with a compatible GPU is fine. You're prototyping, not actually training on it. If you like the one you got then just stick with it.

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macORnvidia OP t1_iv8l6za wrote

Still under that 15 day period. I wanted to get my hands on a machine instead of constantly wondering. What should I look out for to basically validate or discredit my decision over the next week?

Say if it comes to returning it, I'd be down to buying a 32 gb laptop without gpu, but a desktop gpu that I can plug n play and use accordingly.

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arhetorical t1_iv8nb2t wrote

The only thing that matters is if you like it. The specs really don't matter that much. Either you'll be prototyping your model, in which case you'll just be training for an epoch or two and having better specs will only save you a little bit of time, or you'll be training it in which case a laptop is not going to cut it. An external GPU will just make your setup less portable without actually giving you the performance of a workstation.

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macORnvidia OP t1_iv8ssle wrote

>An external GPU will just make your setup less portable without actually giving you the performance of a workstation

Can you please elaborate?

Also, as for training, I get it, I can't really train deep learning models but how about optimizing machine learning models using pyCUDA?

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arhetorical t1_ivb2sl1 wrote

I haven't tried doing that but if it's a similar resource requirement to prototyping (like if you'll be working with a pretrained model, not training one) then it should be fine. Again though, the biggest factor is whether you like it and if it works for you - since you bought a laptop instead of a workstation, you must have had a very good reason for needing one and none of us can answer that question for you. If you're not training, as long as your stuff fits in memory the specs don't matter that much.

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cma_4204 t1_iv9ojml wrote

Laptops are great for prototyping, the one you mentioned will be fine. If you start to work with large models and max it out then just use cloud computing for those large train jobs

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Zer01123 t1_iv9uq1w wrote

For what you want it to do, it is probably more than enough performance. Maybe even an overkill if you just want to play around with deep learning.

Remember that depending on what you want to do, you might need a big SSD for all the datasets, and laptops usually come with quite small ones in the default configuration.

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LevKusanagi t1_ivbfv4f wrote

sorry if not direct advice but i recommend checking tim dettmers' posts on dl hardware. they are probably still relevant today

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LevKusanagi t1_ivbfxgc wrote

if not, you can replicate his testing with current SOTA algos that you care about

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