AIRI and DGX-1 evaluation

 

Try out our AIRI Platform  

Industry’s First Integrated AI-Ready Infrastructure for Deploying Deep Learning at Scale

 

More info about AIRI : https://www.purestorage.com/products/flashblade/ai-infrastructure.html 

 More info about AIRI-Mini: https://www.purestorage.com/company/news-and-events/press/pure-announces-airi-mini.html

More info and documentation on the Nvidia platform for AI Deep Learning and Machine Learning : http://docs.nvidia.com/deeplearning/dgx/bp-dgx/index.html

It's now possible for anyone eligible to test and evaluate the AIRI platform located here in Sweden. To be able to start, please fill out the below form.

Please fill out your answers to the best of your abilities.
Your detailed responses will help CGit to eff ectively assist you ahead of your Proof of Concept.

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Online PoC of DGX-1 qualification

Containerised Frameworks (NVIDIA optimized frameworks for DGX-1 Pascal and/or Volta are DIGITs, Caff e, CUDA, TensorFlow, Caff e2 Theano, MxNet, CNTK, Torch, PyTorch

What data are you planning to use in your application? How large are your datasets? What is the predominant datatype of your data (fixed point, single precision, floating point, double precision floating point, text others?

Onsite DGX-1 POC (Subject to Credit Worthiness and Availability)

Please Note

DGX-1 management network connectivity requires copper ethernet (RJ45 connectors)

DGX-1 requires HTTP access to developer.download.nvidia.com and international.download.nvidia.com for package retrieval

DGX-1 requires HTTPS access to apt.dockerproject.org for Container retrieval

DGX-1 Purchase

By completing and returning this form, you are agreeing that the services offered by CGit are for internal research and development purposes only.
The platform, performance and results must NOT be used for external publications and/or reviews and/or public benchmarks.