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devCUBE™ H₂O - Compact

sysGen devCUBE™ H2O-C – Compact Watercooled Deep Learning Machine

High end deep learning power with up to 4x water cooled NVIDIA® GTX 1080 TI GPUs and Intel Core i7 5930K stays cool and quiet with a complete water cooling system.

Deep Learning is one of the fastest growing and maybe the most exciting area in computing. Advanced neural networks and learning mechanism need absolute high end performance, but not everyone is interested in a loud and big server-rack system. The devCUBE is one of the best deskside solution for deep learning. As a complete system with all required software preinstalled you just need to plug in and start you learning network

Deep Learning is one of the fastest growing and maybe the most exciting area in computing. Advanced neural networks and learning mechanism need absolute high end performance, but not everyone is interested in a loud and big server-rack system. The devCUBE H2O is one of the best deskside solution for deep learning and we are proud to present its even compacter brother:
The devCUBE™ H2O Compact – a sysGen Original

With latest hardware and pre-installed software options the devCUBE stands for an easy entrance and ready-to-go solution for deep learning.



Key Features

Up to 4 NVIDIA Geforce GTX 1080 TI with Pascal Chipset

NVIDIA’s new flagship GeForce GTX 1080 TI is one of the most advanced graphics card ever created. Discover unprecedented performance and power efficiency driven by the new NVIDIA Pascal™ architecture. The devCUBE H2O Compact delivers the power of 4 of these high end cards.


  • 3584 CUDA® Cores
  • 11 GB GDDR5X
  • 484 GB/sec Memory Bandwidth
  • 1582MHz Boost Clock


Water Cooled Hardware

The relevant hardware of the devCUBE H2O is integrated in an advanced water-cooling system. With high quality components from experienced brands we can grant a low maintenance system for silent solution


  • One cycle for all components
  • High quality components only from the best brands
  • Multiple radiators and fans for best cooling and silence
  • Integrated through experienced sysGen-Technicians


Best prepared for Deep Learning

To enable the best possible start in the world of deep learning, we configure and install all relevant software. For an easy user-interface we use Ubuntu as OS. Next to all the frameworks you need, we pre-install and configure the whole NVIDIA package for deep learning and high performance computing. Don't waste time with the software, start researching now.

  • Ubuntu OS
  • NVIDIA DIGITS – Interactive Deep Learning GPU Training System
  • NVIDIA CUDA Deep Learning Neural Network library (cuDNN)*
  • NVIDIA CUDA Toolkit
  • Deep learning frameworks – e.g. Caffe, Torch, Theano and BIDMach

*Before sysGen can install cuDNN , you have to successfully register on the NVIDIA website as a system developer for "Deep Learning" and sign the NVIDIA "CUDA Software Distribution Agreement for Toolkit cuDNN".

€ 9.667,71 (€ 11.504,57 inkl. MwSt.)
Z10-D8 WS Mainboard

High end deep learning power with 4x water cooled NVIDIA® GTX 1080 Ti GPUs and 1x Intel® Core™ i7-6850K / 3.6 GHz Processor stays cool and quiet with a complete water cooling system.

The devCUBE is one of the best deskside solution for deep learning and we are proud to present its even cooler brother: The Compact devCUBE-C H2O – a sysGen Original.


  • Complete watercooled System - silent high-end performance
  • Ready to Go System - completely configured, incl. all required Software
  • NVIDIA DIGITS software providing powerful design, training, and visualization of deep neural networks for image classification
  1. 4x NVIDIA GTX 1080Ti
  2. Intel Core i7-6850K / 3.6 GHz
  3. High level of silent computing with a system wide, low maintenance water cooling system
  4. Pre-Installed and Pre-configured software package for deep learning
  5. Pre-installed Ubuntu with Caffe, Torch, Theano, BIDMach, cuDNN and CUDA
    Pre-requisite: Before sysGen can install cuDNN, you have to successfully register on the NVIDIA website as a system developer for "Deep Learning" and sign the NVIDIA "CUDA Software Distribution Agreement for Toolkit cuDNN".
  6. 64GB Non-ECC DDR4
  7. Storage:
    1x SSD Samsung 850 PRO 512GB SATA III
    3x HDD WD Red 6TB SATA III 6Gb/s