Commit d18f4706 authored by Branislav Jansik's avatar Branislav Jansik

Update introduction.md

parent df9a0683
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......@@ -20,11 +20,11 @@ With NVLink2, it enables 16x Nvidia V100-SXM3 GPUs in a single system, for a tot
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.
Further, the DGX-2 offers a total of ~2 PFLOPs of half precision performance in a single system, when using the tensor cores.
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.
For clustering or further inter-system communications, it also offers InfiniBand and 100GigE connectivity, up to eight of them.
<div align="center">
<iframe src="https://www.youtube.com/embed/OTOGw0BRqK0" width="50%" height="195" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>
Further, the [DGX-2][b] offers a total of ~2 PFLOPs of half precision performance in a single system, when using the tensor cores.
![](../img/dgx1.png)
......@@ -34,16 +34,15 @@ The DGX-2 is able to complete the training process
for FAIRSEQ – a neural network model for language translation – 10x faster than a DGX-1 system,
bringing it down to less than two days total rather than 15 days.
![](../img/dgx3.png)
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.
For clustering or further inter-system communications, it also offers InfiniBand and 100GigE connectivity, up to eight of them.
![](../img/dgx2-nvlink.png)
The new NVSwitches means that the PCIe lanes of the CPUs can be redirected elsewhere, most notably towards storage and networking connectivity.
The topology of the DGX-2 means that all 16 GPUs are able to pool their memory into a unified memory space,
though with the usual tradeoffs involved if going off-chip.
![](../img/dgx2-nvlink.png)
[a]: https://www.nvidia.com/content/dam/en-zz/es_em/Solutions/Data-Center/dgx-2/nvidia-dgx-2-datasheet.pdf
[b]: https://www.youtube.com/embed/OTOGw0BRqK0
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