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
Charted: The Jobs Most Impacted by AI
We visualized the results of an analysis by the World Economic Forum, which uncovered the jobs most impacted by AI.
Charted: The Jobs Most Impacted by AI
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.
Large language models (LLMs) and other generative AI tools haven’t been around for very long, but they’re expected to have far-reaching impacts on the way people do their jobs. With this in mind, researchers have already begun studying the potential impacts of this transformative technology.
In this graphic, we’ve visualized the results of a World Economic Forum report, which estimated how different job departments will be exposed to AI disruption.
Data and Methodology
To identify the job departments most impacted by AI, researchers assessed over 19,000 occupational tasks (e.g. reading documents) to determine if they relied on language. If a task was deemed language-based, it was then determined how much human involvement was needed to complete that task.
With this analysis, researchers were then able to estimate how AI would impact different occupational groups.
Department | Large impact (%) | Small impact (%) | No impact (%) |
---|---|---|---|
IT | 73 | 26 | 1 |
Finance | 70 | 21 | 9 |
Customer Sales | 67 | 16 | 17 |
Operations | 65 | 18 | 17 |
HR | 57 | 41 | 2 |
Marketing | 56 | 41 | 3 |
Legal | 46 | 50 | 4 |
Supply Chain | 43 | 18 | 39 |
In our graphic, large impact refers to tasks that will be fully automated or significantly altered by AI technologies. Small impact refers to tasks that have a lesser potential for disruption.
Where AI will make the biggest impact
Jobs in information technology (IT) and finance have the highest share of tasks expected to be largely impacted by AI.
Within IT, tasks that are expected to be automated include software quality assurance and customer support. On the finance side, researchers believe that AI could be significantly useful for bookkeeping, accounting, and auditing.
Still interested in AI? Check out this graphic which ranked the most commonly used AI tools in 2023.
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