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 PCIe x16. Up to 256GB of RAM and a wide range of storage options.
Quad GPU Rackmount
Full "ML/AI" configuration in a 1U rackmount chassis with up to 4 GPUs at full PCIe x16. Up to 768GB of RAM but limited storage options.
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Machine Learning / AI Information
Our main platform for GPU accelerated Machine Learning applications
- Best workstation configuration for GPU focused workloads like DNN's with TensorFlow or PyTorch
- Also a great system for data science applications in general, even if the focus is on CPU performance
- Highest quality motherboard
- 4 Full x16, PLX switched, metal reinforced PCIe slots
- Optimal chassis with excellent cooling and quiet operation
Recommended hardware configs (other options available)
- 2x RTX 3080 or 3090, 4x RTX A6000
- Intel Xeon-W 2255 10-core or Xeon-W 2295 18-core
- 128 or 256GB memory
- 1TB system SSD, 2TB data SSD, 4GB storage HD
Note: Some workloads may not scale well on multiple GPUs. You might consider using 2 GPUs to start with unless you are confident that your particular usage and job characteristics will scale to 4 cards. In some configurations, we can pre-wire for additional cards for easy expansion. If you are using Tensorflow, multi-GPU scaling is generally very good.
Why Choose Puget Systems?
Rather than getting a generic workstation, our systems are designed around your unique workflow and are optimized for the work you do every day.
We make sure our representatives are as accessible as possible, by phone and email. At Puget Systems, you can actually talk to a real person!
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