According to calculations by the IEEE, in a paper about the Google cluster, a rack with 88 dual-CPU machines used to cost about $278,000. If you divide the $250 million figure from the S-1 filing by $278,000, you end up with a bit over 899 racks. Assuming that each rack holds 88 machines, you end up with 79,000 machines.
However, one must recognize that equipment is not all CPUs. As a result, you must discount the figure of $250 million to account for routers, firewalls, machines for employees, etc… So let’s assume for a minute that only about $200 million is going to the CPUs. That still leaves us with 719 racks or a bit over 63,000 machines.
Even if we discount other equipment to be costing $100 million, we end up with a bit over 31,654 machines on 359 racks.
So how much processing power is that? Well, once again, the Google cluster document provides some interesting tidbits. Per the document, the racks that were used were
88 dual-CPU 2 Ghz Intel Xeon servers with 2 Gbytes of RAM and an 80-Gbytes hard disk.
That means that, on the low end, the Google cluster has the following stats:
- 359 racks
- 31,654 machines
- 63,184 CPUs
- 126,368 Ghz of processing power
- 63,184 Gb of RAM
- 2,527 Tb of Hard Drive space
In the middle range of my estimates, the cluster would have:
- 719 racks
- 63,272 machines
- 126,544 CPUs
- 253,088 Ghz of processing power
- 126,544 Gb of RAM
- 5,062 Tb of Hard Drive space
And on the high end of my estimates:
- 899 racks
- 79,112 machines
- 158,224 CPUs
- 316,448 Ghz of processing power
- 158,224 Gb of RAM
- 6,180 Tb of Hard Drive space
Assuming that the 1Ghz chip is going at about a third the gigaflops of a 2Ghz processor (3.3Gflops), we can then guess at the size of the Google supercomputer. Just for the sake of argument, let’s go with 1 Gigaflop per processor. This means that the Google supercomputer has about 126 teraflops of power on the low end of my estimates, 253 teraflops on the middle end, and 316 teraflops on the high end. This would easily put it on top of the list of fastest computers in the world.
Any way you slice it, that’s a lot of power.