EricPB
June 20, 2017, 6:50pm
4
I agree with @natedl98 : why not try the dual-boot path first ?
I went that way with a desktop PC-Gaming rig from mid-2015, you can see its specs here:
Hello everyone !
Just sharing my own GTX 1080Ti results for @jeremy “mnist.ipynb” notebook from Lesson 4 (BatchNorm + Dropout + Data Augmentation) he was running on last-gen GTX TITAN X.
In the last 12_epoch run (cell #85), I get 9-10 sec per epoch vs. his 13-14 sec so a basic 30% speed gain.
My rig is a former gaming PC from mid-2015:
Gigabyte Z97X motherboard with 16Gb DDR3 1866mhz (reused from a 2012 rig ^!^ )
Intel I5-4690K 3.5Ghz, not overclocked
Corsair CX 650M PSU
Samsung SSD Seri…
Some tips, based on my own experience, if you go that way:
Have you considered a dual-boot Win10 and Ubuntu 16.04 ?
It’s pretty easy to install and will give you access to a wider range of “stable” machine learning tools.
Plus you’ll have to switch to Ubuntu for Part 2 down the road.
Pro-tip: make sure to keep a Win10 installation DVD or USB for the day you decide to uninstall your Ubuntu partition, as you’ll need it to repair/restore your boot manager
A quick update for those using epoch time on Cell #7 of lesson1.ipynb as a benchmark for setup (@RogerS49 , @stephenl , @kzuiderveld , @brendan ).
After upgrading to Python 3.6 and Keras 2.0 for Part #2 (Part #1 use Python 2.7 and Keras 1.22), I used @Robi updated notebooks.
Took just a few minutes to finetune file names here and there. like utils_p3.py, vvg16_p3.py etc
And I agree -again- with @natedl98 : once I experienced Ubuntu, I barely looked back.
I only reboot to Windows for gaming, as the best games (I’m hardcore on Blizzard, was a No-Life multi-boxing on WoW a decade ago ^!^) and their ecosystem (add-ons) only run on Windows.
E.
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