Nvidia DGX-1 uses eight Tesla P100s to speed up deep learning

Holy mother of GPUs. If you've been reading the news today, then you know Nvidia has launched the Tesla P100, the HPC equivalent of the Schwerer Gustav mega-cannon. But really, who wants just one of those cards for crunching tons and tons of deep-learning data? Take a good look at Nvidia's DGX-1 Deep Learning System.

Nvidia claims the DGX-1 is the "world's first deep-learning supercomputer in a box." It includes eight Tesla P100 cards, all meshed together with the NVLink interconnect. According to Nvidia, the DGX-1 could be 75 times faster than a dual-socket Xeon E5-2697 v3 CPU system when running neural network training tasks, and it can perform up to 170 TFLOPS—a claimed 56 times the performance of the same pair of Xeons. The company says deep-learning users can expect as much as a 12-fold speedup in neural-network training tasks with the DGX-1 compared to a server with four Maxwell chips inside.

There are some other meaty numbers to go with those claims. The DGX-1's Tesla GP100s each have 16GB of HBM2 RAM to work with. The main system is powered by two 16-core Intel Xeon E5-2698 v3 CPUs and 512GB of DDR4 RAM. A RAID-0 array of four 1.92-TB SSDs and dual 10GbE ports round out the main specs. The unit's maximum power draw is rated at a whopping 3200W. Nvidia says interested parties can order a DGX-1 today for $129,000.

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