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.
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?
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
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.