Exxact Valence VWS-1735800-DPW 1x Intel Xeon W processor - Deep Learning & AI Workstation

MPN: VWS-1735800-DPW
VWS-1735800-DPW
Highlights
  • Form Factor: Mid-Tower
  • Processor: 1x Intel Xeon W processor
  • Drive Bays: 2x 5.25" External, 4x 2.5" Internal, 2x 2.5"/3.5" Internal
  • Supports up to 4x Double-Wide cards
VWS-1735800-DPW
VWS-1735800-DPW
VWS-1735800-DPW
VWS-1735800-DPW

Exxact Valence VWS-1735800-DPW 1x Intel Xeon W processor - Deep Learning & AI Workstation

MPN: VWS-1735800-DPW
Highlights
  • Form Factor: Mid-Tower
  • Processor: 1x Intel Xeon W processor
  • Drive Bays: 2x 5.25" External, 4x 2.5" Internal, 2x 2.5"/3.5" Internal
  • Supports up to 4x Double-Wide cards

The Valence VWS-1735800-DPW is a Deep Learning & AI Workstation supporting 1x Intel Xeon W processor, a maximum of 1 TB DDR4 memory, and up to 4x Double-Wide cards.

The World's Fastest Deep Learning Workstation Right at Your Desk

GPUs have provided groundbreaking performance to accelerate deep learning research with thousands of computational cores and up to 100x application throughput when compared to CPUs alone. Exxact has developed the Deep Learning Workstation, featuring NVIDIA GPU technology coupled with state-of-the-art PCIe peer to peer interconnect technology, and a full pre-installed suite of the leading deep learning software, for developers to get a jump-start on deep learning research with the best tools that money can buy.

Features:

  • NVIDIA DIGITS software providing powerful design, training, and visualization of deep neural networks for image classification
  • Pre-installed standard Ubuntu 18.04/20.04 w/ Exxact Machine Learning Image (EMLI)
  • Google TensorFlow software library
  • Automatic software update tool included
  • A turn-key workstation with superior PCIe peer to peer topology

An EMLI Environment for Every Developer

Conda EMLI

Conda EMLI

Separated Frameworks

For developers who want pre-installed deep learning frameworks and their dependencies in separate Python environments installed natively on the system.


Container EMLI

Container EMLI

Flexible. Reconfigurable.

For developers who want pre-installed frameworks utilizing the latest NGC containers, GPU drivers, and libraries in ready to deploy DL environments with the flexibility of containerization.


DIY EMLI

DIY EMLI

Simple. Clean. Custom.

For experienced developers who want a minimalist install to set up their own private deep learning repositories or custom builds of deep learning frameworks.