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Bitcoin network faster than top 500 supercomputers combined

The Bitcoin network, which is operated by computers conducting bitcoin mining, has passed 1 exaFLOPS, making it more than 8 times faster than the top 500 super computers combined.

FLOPS  is an abbreviation of FLoating-point Operations Per Second, and is a common measure of a computer’s speed. According to bitcoinwatch.com, the hashrate estimate for the bitcoin network has just passed 1 exaFLOPS (or 1000 petaFLOPS). This is technically not an accurate measurement since bitcoin mining, the process which maintains the bitcoin network, uses almost no floating point operations, relying entirely on integer calculations instead. Thus, the number is more of an estimate. Still, this puts the speed of the network somewhere in the range of 8 times faster than the top 500 supercomputers in the world… combined.

IBM Sequoia, the world's fastest super computer


The FLOPS estimate is based on the cost for a system to do bitcoin hash operations on its graphics card, rather than perform other tasks. A conversion rate of 1 hash = 12.7K FLOPS is used to determine the general speed of the network contribution. The estimate was created in 2011, before the creation of ASIC hardware solely designed for bitcoin mining. ASIC doesn’t use floating point operations at all, so there is no “cost” for the system to draw from. Thus, the estimate doesn’t have any real-world meaning for such hardware.


Still, an exaFLOPS is an impressive number, regardless of whether it is technically correct. Top500.org maintains a list of the 500 fastest super computers in the world. The top ranking computer, IBM’s Sequoia, can manage about 16.3 petaFLOPS, or 1.6% of the bitcoin network speed. If all 500 computers were combined, they’d have 48 petaFLOPS between then, which is amazingly, only 5% of what bitcoin is using.

David F.
A grad student in experimental physics, David is fascinated by science, space and technology. When not buried in lecture books, he enjoys movies, gaming and mountainbiking

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