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Recommended Systems for Machine Learning / AI TensorFlow


Configure a Machine Learning / AI Workstation

Quad GPU Workstation

Full "ML/AI" configuration using our highest quality motherboard with up to 4 GPUs at full X16. Up to 256GB of RAM and a wide range of storage options.

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 Machine Learning / AI GPU Workstation

  • Updated version of our  "DIGITS" workstation
  • Best workstation configuration for GPU focused workloads like DNN's with TensorFlow or PyTorch 
  • Can train GoogLeNet on a 1 million ImageNet subset for 30 epocs in under 8hr
  • Highest quality motherboard
    • 4 Full X16, PLX switched, metal reinforced PCIe slots
  • Optimal chassis with excellent cooling and quiet operation

Our main platform for GPU accelerated Machine Learning applications 

  • Recommended hardware configs ( other options available )
    • 2 or 4 RTX 2080Ti, RTX 2070, or Titan V  GPU's
    • Intel Xeon-W 2145 8-core or Xeon-W 2195 18-core
    • 128 or 256GB memory
    • 1TB system SSD, 2TB data SSD, 4GB storage HD

We have trained deep neural networks with complex models and large data sets, utilizing 4 Titan-V GPU's with this system.

Note: Some workloads may not scale well on multiple GPU's You might consider using 2 GPU's to start with unless you are confident that your particular usage and job characteristics will scale to 4 cards. We can pre-wire for 4 cards for easy expansion.  If you are using Tensorflow multi-GPU scaling is generally very good.


Looking for more detail on our testing and why we chose this hardware? Have a look at the testing blog post!

NVIDIA DIGITS, Caffe, and Machine Learning Articles: