Technology
Visualizing the Power of the World’s Supercomputers
Visualizing the Power of the World’s Supercomputers
A supercomputer is a machine that is built to handle billions, if not trillions of calculations at once. Each supercomputer is actually made up of many individual computers (known as nodes) that work together in parallel.
A common metric for measuring the performance of these machines is flops, or floating point operations per second.
In this visualization, we’ve used November 2021 data from TOP500 to visualize the computing power of the world’s top five supercomputers. For added context, a number of modern consumer devices were included in the comparison.
Ranking by Teraflops
Because supercomputers can achieve over one quadrillion flops, and consumer devices are much less powerful, we’ve used teraflops as our comparison metric.
1 teraflop = 1,000,000,000,000 (1 trillion) flops.
Rank | Name | Type | Teraflops |
---|---|---|---|
#1 | 🇯🇵 Supercomputer Fugaku | Supercomputer | 537,212 |
#2 | 🇺🇸 Summit | Supercomputer | 200,795 |
#3 | 🇺🇸 Sierra | Supercomputer | 125,712 |
#4 | 🇨🇳 Sunway Taihulight | Supercomputer | 125,436 |
#5 | 🇺🇸 Perlmutter | Supercomputer | 93,750 |
n/a | Nvidia Titan RTX | Consumer device | 130 |
n/a | Nvidia GeForce RTX 3090 | Consumer device | 36 |
n/a | Xbox Series X | Consumer device | 12 |
n/a | Tesla Model S (2021) | Consumer device | 10 |
Supercomputer Fugaku was completed in March 2021, and is officially the world’s most powerful supercomputer. It’s used for various applications, including weather simulations and innovative drug discovery.
Sunway Taihulight is officially China’s top supercomputer and fourth most powerful in the world. That said, some experts believe that the country is already operating two much more powerful systems, based on data from anonymous sources.
As you can see, the most advanced consumer devices do not come close to supercomputing power. For example, it would take the combined power of 4,000 Nvidia Titan RTX graphics cards (the most powerful consumer card available) to measure up to the Fugaku.
Upcoming Supercomputers
One of China’s unrevealed supercomputers is supposedly named Oceanlite, and is a successor to Sunway Taihulight. It’s believed to have reached 1.3 exaflops, or 1.3 quintillion flops. The following table makes it easier to follow all of these big numbers.
Name | Notation | Exponent | Prefix |
---|---|---|---|
Quintillion | 1,000,000,000,000,000,000 | 10^18 | Exa |
Quadrillion | 1,000,000,000,000,000 | 10^15 | Peta |
Trillion | 1,000,000,000,000 | 10^12 | Tera |
Billion | 1,000,000,000 | 10^9 | Giga |
Million | 1,000,000 | 10^6 | Mega |
In the U.S., rival chipmakers AMD and Intel have both won contracts from the U.S. Department of Energy to build exascale supercomputers. On the AMD side, there’s Frontier and El Capitan, while on the Intel side, there’s Aurora.
Also involved in the EL Capitan project is Hewlett Packard Enterprise (HPE), which claims the supercomputer will be able to reach 2 exaflops upon its completion in 2023. All of this power will be used to support several exciting endeavors:
- Enable advanced simulation and modeling to support the U.S. nuclear stockpile and ensure its reliability and security.
- Accelerate cancer drug discovery from six years to one year through a partnership with pharmaceutical company, GlaxoSmithKline
- Understand the dynamic and mutations of RAS proteins that are linked to 30% of human cancers
Altogether, exascale computing represents the ability to conduct complex analysis in a matter of seconds, rather than hours. This could unlock an even faster pace of innovation.
Technology
Visualizing AI Patents by Country
See which countries have been granted the most AI patents each year, from 2012 to 2022.
Visualizing AI Patents by Country
This was originally posted on our Voronoi app. Download the app for free on iOS or Android and discover incredible data-driven charts from a variety of trusted sources.
This infographic shows the number of AI-related patents granted each year from 2010 to 2022 (latest data available). These figures come from the Center for Security and Emerging Technology (CSET), accessed via Stanford University’s 2024 AI Index Report.
From this data, we can see that China first overtook the U.S. in 2013. Since then, the country has seen enormous growth in the number of AI patents granted each year.
Year | China | EU and UK | U.S. | RoW | Global Total |
---|---|---|---|---|---|
2010 | 307 | 137 | 984 | 571 | 1,999 |
2011 | 516 | 129 | 980 | 581 | 2,206 |
2012 | 926 | 112 | 950 | 660 | 2,648 |
2013 | 1,035 | 91 | 970 | 627 | 2,723 |
2014 | 1,278 | 97 | 1,078 | 667 | 3,120 |
2015 | 1,721 | 110 | 1,135 | 539 | 3,505 |
2016 | 1,621 | 128 | 1,298 | 714 | 3,761 |
2017 | 2,428 | 144 | 1,489 | 1,075 | 5,136 |
2018 | 4,741 | 155 | 1,674 | 1,574 | 8,144 |
2019 | 9,530 | 322 | 3,211 | 2,720 | 15,783 |
2020 | 13,071 | 406 | 5,441 | 4,455 | 23,373 |
2021 | 21,907 | 623 | 8,219 | 7,519 | 38,268 |
2022 | 35,315 | 1,173 | 12,077 | 13,699 | 62,264 |
In 2022, China was granted more patents than every other country combined.
While this suggests that the country is very active in researching the field of artificial intelligence, it doesn’t necessarily mean that China is the farthest in terms of capability.
Key Facts About AI Patents
According to CSET, AI patents relate to mathematical relationships and algorithms, which are considered abstract ideas under patent law. They can also have different meaning, depending on where they are filed.
In the U.S., AI patenting is concentrated amongst large companies including IBM, Microsoft, and Google. On the other hand, AI patenting in China is more distributed across government organizations, universities, and tech firms (e.g. Tencent).
In terms of focus area, China’s patents are typically related to computer vision, a field of AI that enables computers and systems to interpret visual data and inputs. Meanwhile America’s efforts are more evenly distributed across research fields.
Learn More About AI From Visual Capitalist
If you want to see more data visualizations on artificial intelligence, check out this graphic that shows which job departments will be impacted by AI the most.
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