Security of data is crucial for many applications and often you would need to run experiments locally at your company whenever you deal with sensitive data. That’s why a perfect solution will be buying a workstation. There are many specialised machine learning workstations available on the market currently and in this text I will review some of them.
Top Machine Learning Workstations
My list covers top 3 machine learning workstations available on the market right now. Choosing a workstation will depend on your applications and budget.
This piece of hardware is an awesome looking, great performing deep learning workstation made by Lambda, a company specialized in hardware for machine learning experiments. With its affordable pricing, it’s a great way to build your company’s computing power. And now it also features the newest GPUs from RTX 30 series.
- Up to 4x GPUs. Choose from RTX 3090, 3080, 3070, Quadro RTX 8000, and Quadro RTX 6000.
- Up to 256 GB of memory.
- AMD Threadripper or Intel Core i9 CPU.
- 2 TB NVMe.
- Starts at $5,408.
NVIDIA® DGX Station™ is the world’s first purpose-built AI workstation, powered by four NVIDIA Tesla® V100 GPUs. It delivers 500 teraFLOPS (TFLOPS) of deep learning performance — the equivalent of hundreds of traditional servers — conveniently packaged in a workstation form factor built on NVIDIA NVLink™ technology.
Truly an enterprise-grade solution and a welcome gift for any machine learning team.
Featuring a 14-core, high-performance Intel Xeon W processor, up to four GPUs, and 512GB DDR4–2666MHz, the HyperStation DLX-4R allows developers and researchers to experiment on models of a more complicated nature, using much larger data sets.
- Intel Xeon W-2175 2.5Hz (4.3GHz Turbo) 14 Core Processor
- 4x NVIDIA RTX 2080 Ti Turbo 11GB Graphics (4352 CUDA Cores per GPU)
- 128GB ECC DDR4 2666MHz quad-channel Memory
- 512GB NVMe M.2 SSD + 2x 4TB Enterprise-class HDD
- Support for up to 4 double-width GPUs @ PCIe x16 (PLX switched)
- 2x 10 Gigabit Ethernet
Build a deep learning workstation yourself
The last option you might want to consider when you need a workstation but you are on a budget is building one yourself. You need to be highly technical to do that, but it might be worth it.
Have a look at this tutorial here if you want to build your own machine learning workstation.
Which workstation to buy for machine learning?
For the final decision which workstation to choose for your machine learning experiments, you need to evaluate properly how big models you will run. Based on that you can look at the parameters of these workstations to choose the one with enough computing power.