The new DGX SaturnV contains 60,512 CPU cores (the machine relies on Intel’s Xeon E5-2698v4 for its CPUs) and 63,488GB of RAM. The machine is actually a cluster of 125 DGX-1 systems — that’s the AI processing “supercomputer in a box” that Nvidia unveiled last year, and the first machine to feature the company’s Pascal GPUs (the full GP100 configuration). According to Nvidia, the new machine is 2.3x more energy efficient than the closest Xeon Phi system of equivalent performance and it delivers 9.46GFLOPS/watt, a 42% improvement over the most efficient system unveiled last June. That’s a huge improvement in a relatively short period of time, though I do want to note an important caveat to these kinds of figures. One thing we’ve covered before in our previous discussions of exascale computing is how ramping compute clusters upwards creates very different constraints than we typically consider when talking about desktops or even servers. Factors like interconnect power consumption, total memory loadout, and memory architecture all play a significant part in how these metrics play out.