AI Development Workstations
- Filtered by : "Deep Learning" and "Development"
ProStation WX9-QR4
Powered by the Intel i9-10900X with a boost clock of 4.5GHz and 20 Threads, The ProStation WX9-QR4 is optimised for deep-learning development, where models can be created and optimised at an affordable workstation level.
With dual Professional Quadro RTX or Tesla graphics and up to 128GB of memory, the WX9-QR4 offers an excellent platform for Deep Learning Development. All of our systems are thoroughly tested for any potential thermal throttling and are available pre-installed with Ubuntu, and any framework you require, including CUDA, DIGITS, Caffe Pytorch, Tensorflow, Theano, and Torch.
- Ideal for Media, Product Design, AEC and DL Workflows
- up to 128GB DDR4 Memory
- up to Dual Quadro RTX Graphics
- Customisable Storage & Networking Solutions
- 3 Years Return-to-Base Warranty
Order code: PC-2701
Select Operating System
No operating system
Built to Order
£2640.00
£2200.00 ex VAT
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ProStation WTP-VII
Powered by the AMD Ryzen Threadripper Pro 3955WX with a boost clock of 4.3GHz, 32 Threads and 128 PCIe 4.0 lanes for increased bandwidth, the ProStation WTP-VII is optimised for deep-learning development, where models can be created and optimised at an affordable workstation level.
With up to dual Professional Quadro RTX or Tesla graphics and up to 128GB of ECC RDIMM memory, the WTP-VII offers an excellent platform for Deep Learning Development.
All of our systems are thoroughly tested for any potential thermal throttling and are available pre-installed with Ubuntu, and any framework you require, including CUDA, DIGITS, Caffe Pytorch, Tensorflow, Theano, and Torch.
- Ideal for AEC, and DL Workflows
- up to 256GB DDR4 ECC Memory
- up to Quad Quadro RTX or Tesla Graphics
- Customisable Storage & Networking Solutions
- 3 Years Return-to-Base Warranty
Order code: PC-2765
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No operating system
Built to Order
£4380.00
£3650.00 ex VAT
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ProStation WXW3-QR5
Powered by the Intel Xeon W-3223 with a boost clock of 4.0GHz, 16 Threads, and 64 PCIe lanes, The ProStation WXW3-QR5 is optimised for deep-learning development, where models can be created and optimised at an affordable workstation level.
With
up to Quad Professional Quadro RTX or Tesla graphics and up to 256GB of memory, the WT3-QR5 offers an excellent platform for Deep Learning Development and Training.
All of our systems are thoroughly tested for any potential thermal throttling
and are available pre-installed with Ubuntu, and any framework you require, including CUDA, DIGITS, Caffe Pytorch, Tensorflow, Theano, and Torch
- Ideal for Product Design, AEC, and DL Workflows
- up to 256GB DDR4 Memory
- up to Quad Quadro RTX or Tesla Graphics
- Customisable Storage & Networking Solutions
- 3 Years Return-to-Base Warranty
Order code: PC-2706
Select Operating System
No operating system
Built to Order
£4440.00
£3700.00 ex VAT
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NVIDIA DGX Station
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. NVIDIA DGX Station is water-cooled and whisper-quiet, fitting neatly under your desk. It also uses the same NVIDIA GPU Cloud Deep Learning Software Stack powering all NVIDIA DGX™ solutions, so developers and researchers can experiment and tune their models, iterate fast, and deploy their work effortlessly on a DGX in the data center for larger-scale production training.
DGX Station is a great solution for organisations that want an integrated hardware and software solution, with full-stack optimisation for maximised performance and NVIDIA’s enterprise-grade support to keep you up and running.
- 1st year SUMS Support Package
- Intel Xeon Processor E5-2698 v4
- 256GB DDR4 RDIMM Memory
- 4 x 1.92 TB SSD RAID 0
- 4 x NVIDIA Tesla V100 32GB GDDR5
Order code: SR-0260
Configured Server from :
Built to Order - Approximately 7 Days
£56999.00
£47499.17 ex VAT
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