Building a Deep Learning (Dream) Machine: DIY hardware hacking for the uninitiated. Talk given at Data Science London Meetup. 27 June 2016

1. Building a Deep
Learning (Dream)
Machine
DIY hardware hacking for the uninitiated
Roelof Pieters
@graphific http://www.graph-technologies.com
27 June 2016

6. http://graphific.github.io/

7. How: Machine Thank you gamers!

8. Why
- Cheaper *
- Can do things you can’t do in the cloud
- Desktop = faster experiment iteration
- Remote still possible
- Customize to your own needs
- Fun!
* in my own particular case

9. Points to think about
- How many GPUs now and later
- Motherboard (40 lanes / 16x8x8x8 configuration for 4 GPUs)
- Chassis with enough space + air flow
- 4 GPUs: 7 PCIe slots (last GPU can be mounted at the bottom using only one
slot)
- CPU: good enough, as much cores as GPUs, make sure CPU supports 40
PCIe lanes, some new Haswell CPUs only support 32;
- RAM: 2x of total GPU memory
- SSD = nice if data doesn’t fit into GPU+RAM (or hdfs reads from disk): get
larger SSD than your largest dataset
- Mechanical disks: plenty of storage
- PSU: don’t save on efficiency (titanium/platinum)
- Cooling: Water (hard diy) or Fan (easy/cheap but noisy)

11. I: HARDWARE

12. How: Machine

13. How: Machine

14. How: Machine (2)

21. II: SOFTWARE

28. https://github.
com/deeplearningpari
s/dl-machine

29. And so on...

31. http://gitxiv.com/

32. http://www.creativeai.net/

35. GTX 1080

36. Drive PX 2
P100

39. EPGU

40. PGU

42. READ MORE

43. http://graphific.github.io/

44. https:
//hackaday.
io/project/1207
0-32-tflop-
deep-learning-
gpu-box

45. http://timdettmers.
com/2015/03/09/dee
p-learning-
hardware-guide/

46. https://timdettmers.
wordpress.
com/2014/08/14/whi
ch-gpu-for-deep-
learning/