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