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Key Highlights from GTC DC 2018
CYXTERA JOINS
THE FIGHT
AGAINST COVID-
19
Cyxtera Donates DGX-1 and
DGX-2 Compute Cycles to
Folding@Home Initiative
“NVIDIA DGX-2 – as one of the world's
most powerful GPU compute platforms
– is ideally suited for the most complex
compute challenges such as the one
we’re facing now in the race to find
answers about COVID-19.”
-HOLLAND BARRY
Cyxtera
source: https://www.thestreet.com/investing/nvidia-is-leading-the-a-i-revolution-14754500
Cyxtera
Source : https://www.nvidia.com/en-us/gtc/session-catalog-details/?#/&ncid=so-link-48306&sfdcid=IX03#cid=ix03_so-link_en-us
To assist in the race for a cure for COVID-19,
Cyxtera has donated GPU cycles on NVIDIA DG
and DGX-2 systems to the Folding@Home pro
➢ Cyxtera’s donated cycles are in the top 1% of
supporting the project worldwide
➢ Folding@Home has crowdsourced over 1 exafl
processing power, or 1,000,000,000,000,000,0
operations per second
➢ Data Augmentation and Segmentation with
Generative Networks for Medical Imaging
Learn More

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Cyxtera Joins the Fight Against COVID-19 with NVIDIA DGX

  • 1. Key Highlights from GTC DC 2018 CYXTERA JOINS THE FIGHT AGAINST COVID- 19 Cyxtera Donates DGX-1 and DGX-2 Compute Cycles to Folding@Home Initiative
  • 2. “NVIDIA DGX-2 – as one of the world's most powerful GPU compute platforms – is ideally suited for the most complex compute challenges such as the one we’re facing now in the race to find answers about COVID-19.” -HOLLAND BARRY Cyxtera source: https://www.thestreet.com/investing/nvidia-is-leading-the-a-i-revolution-14754500
  • 3. Cyxtera Source : https://www.nvidia.com/en-us/gtc/session-catalog-details/?#/&ncid=so-link-48306&sfdcid=IX03#cid=ix03_so-link_en-us To assist in the race for a cure for COVID-19, Cyxtera has donated GPU cycles on NVIDIA DG and DGX-2 systems to the Folding@Home pro ➢ Cyxtera’s donated cycles are in the top 1% of supporting the project worldwide ➢ Folding@Home has crowdsourced over 1 exafl processing power, or 1,000,000,000,000,000,0 operations per second ➢ Data Augmentation and Segmentation with Generative Networks for Medical Imaging Learn More