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Commit 9bd112ce authored by Jan Siwiec's avatar Jan Siwiec
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Update introduction.md

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4 merge requests!368Update prace.md to document the change from qprace to qprod as the default...,!367Update prace.md to document the change from qprace to qprod as the default...,!366Update prace.md to document the change from qprace to qprod as the default...,!323extended-acls-storage-section
# NVIDIA DGX-2
The DGX-2 is a very powerful computational node, featuring high end x86_64 processors and 16 Nvidia V100-SXM3 GPUs.
The DGX-2 is a very powerful computational node, featuring high end x86_64 processors and 16 NVIDIA V100-SXM3 GPUs.
| NVIDIA DGX-2 | |
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The [DGX-2][a] introduces NVIDIA’s new NVSwitch, enabling 300 GB/s chip-to-chip communication at 12 times the speed of PCIe.
With NVLink2, it enables 16x Nvidia V100-SXM3 GPUs in a single system, for a total bandwidth going beyond 14 TB/s.
With NVLink2, it enables 16x NVIDIA V100-SXM3 GPUs in a single system, for a total bandwidth going beyond 14 TB/s.
Featuring pair of Xeon 8168 CPUs, 1.5 TB of memory, and 30 TB of NVMe storage,
we get a system that consumes 10 kW, weighs 163.29 kg, but offers double precision perfomance in excess of 130TF.
we get a system that consumes 10 kW, weighs 163.29 kg, but offers double precision performance in excess of 130TF.
The DGX-2 is designed to be a powerful server in its own right.
On the storage side the DGX-2 comes with 30TB of NVMe-based solid state storage.
On the storage side, the DGX-2 comes with 30TB of NVMe-based solid state storage.
For clustering or further inter-system communications, it also offers InfiniBand and 100GigE connectivity, up to eight of them.
Further, the [DGX-2][b] offers a total of ~2 PFLOPs of half precision performance in a single system, when using the tensor cores.
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