|
gptkbp:instance_of
|
gptkb:computer
|
|
gptkbp:aims_to
|
accelerate AI development
|
|
gptkbp:designed_for
|
gptkb:AI_technology
|
|
gptkbp:features
|
gptkb:NVIDIA_GPUs
multi-GPU configurations
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
NVIDIA DGX family
|
|
gptkbp:includes
|
gptkb:DGX-2
gptkb:DGX_Super_POD
gptkb:DGX-1
gptkb:DGX_A100
gptkb:DGX_Station
|
|
gptkbp:integrates_with
|
gptkb:NVIDIA_NGC
|
|
gptkbp:is_available_in
|
various configurations
|
|
gptkbp:is_compatible_with
|
gptkb:Tensor_Flow
gptkb:Caffe
gptkb:Chainer
gptkb:MXNet
gptkb:Py_Torch
|
|
gptkbp:is_known_for
|
high performance
scalability
robustness
ease of use
|
|
gptkbp:is_optimized_for
|
machine learning workloads
|
|
gptkbp:is_part_of
|
gptkb:NVIDIA_AI_platform
NVIDIA's AI ecosystem
|
|
gptkbp:is_promoted_by
|
NVIDIA marketing
|
|
gptkbp:is_supported_by
|
NVIDIA's software stack
|
|
gptkbp:is_targeted_at
|
gptkb:researchers
academics
data scientists
machine learning engineers
AI developers
|
|
gptkbp:is_used_by
|
research institutions
enterprise companies
|
|
gptkbp:is_used_in
|
gptkb:cloud_computing
edge computing
|
|
gptkbp:marketed_as
|
gptkb:Data_Analytics
AI infrastructure
deep learning platform
AI supercomputing platform
high-performance computing platform
|
|
gptkbp:offers
|
scalable architecture
|
|
gptkbp:produced_by
|
gptkb:NVIDIA
|
|
gptkbp:provides
|
high-performance computing
high-speed interconnects
end-to-end AI solutions
|
|
gptkbp:released_in
|
gptkb:2016
|
|
gptkbp:supports
|
gptkb:NVIDIA_CUDA
deep learning frameworks
AI inference
AI training
|
|
gptkbp:used_in
|
data centers
|
|
gptkbp:bfsParent
|
gptkb:DGX-1
gptkb:NVIDIA's_DGX_A100_system
|
|
gptkbp:bfsLayer
|
6
|