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.
|#1||🇯🇵 Supercomputer Fugaku||Supercomputer||537,212|
|#4||🇨🇳 Sunway Taihulight||Supercomputer||125,436|
|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.
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.
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.
Every Mission to Mars in One Visualization
This graphic shows a timeline of every mission to Mars since 1960, highlighting which ones have been successful and which ones haven’t.
Timeline: A Historical Look at Every Mission to Mars
Within our Solar System, Mars is one of the most similar planets to Earth—both have rocky landscapes, solid outer crusts, and cores made of molten rock.
Because of its similarities to Earth and proximity, humanity has been fascinated by Mars for centuries. In fact, it’s one of the most explored objects in our Solar System.
But just how many missions to Mars have we embarked on, and which of these journeys have been successful? This graphic by Jonathan Letourneau shows a timeline of every mission to Mars since 1960 using NASA’s historical data.
A Timeline of Mars Explorations
According to a historical log from NASA, there have been 48 missions to Mars over the last 60 years. Here’s a breakdown of each mission, and whether or not they were successful:
|1||1960||Korabl 4||USSR (flyby)||Failure|
|2||1960||Korabl 5||USSR (flyby)||Failure|
|3||1962||Korabl 11||USSR (flyby)||Failure|
|4||1962||Mars 1||USSR (flyby)||Failure|
|5||1962||Korabl 13||USSR (flyby)||Failure|
|6||1964||Mariner 3||US (flyby)||Failure|
|7||1964||Mariner 4||US (flyby)||Success|
|8||1964||Zond 2||USSR (flyby)||Failure|
|11||1969||Mariner 6||US (flyby)||Success|
|12||1969||Mariner 7||US (flyby)||Success|
|15||1971||Mars 2 Orbiter/Lander||USSR||Failure|
|16||1971||Mars 3 Orbiter/Lander||USSR||Success/Failure|
|20||1973||Mars 6 Orbiter/Lander||USSR||Success/Failure|
|21||1973||Mars 7 Lander||USSR||Failure|
|22||1975||Viking 1 Orbiter/Lander||US||Success|
|23||1975||Viking 2 Orbiter/Lander||US||Success|
|24||1988||Phobos 1 Orbiter||USSR||Failure|
|25||1988||Phobos 2 Orbiter/Lander||USSR||Failure|
|27||1996||Mars Global Surveyor||US||Success|
|31||1998||Mars Climate Orbiter||US||Failure|
|32||1999||Mars Polar Lander||US||Failure|
|33||1999||Deep Space 2 Probes (2)||US||Failure|
|35||2003||Mars Express Orbiter/Beagle 2 Lander||ESA||Success/Failure|
|36||2003||Mars Exploration Rover - Spirit||US||Success|
|37||2003||Mars Exploration Rover - Opportunity||US||Success|
|38||2005||Mars Reconnaissance Orbiter||US||Success|
|39||2007||Phoenix Mars Lander||US||Success|
|40||2011||Mars Science Laboratory||US||Success|
|42||2013||Mars Atmosphere and Volatile Evolution||US||Success|
|43||2013||Mars Orbiter Mission (MOM)||India||Success|
|44||2016||ExoMars Orbiter/Schiaparelli EDL Demo Lander||ESA/Russia||Success/Failure|
|45||2018||Mars InSight Lander||US||Success|
|47||2020||Tianwen-1 Orbiter/Zhurong Rover||China||Success|
|48||2020||Mars 2020 Perseverance Rover||US||Success|
The first mission to Mars was attempted by the Soviets in 1960, with the launch of Korabl 4, also known as Mars 1960A.
As the table above shows, the voyage was unsuccessful. The spacecraft made it 120 km into the air, but its third-stage pumps didn’t generate enough momentum for it to stay in Earth’s orbit.
For the next few years, several more unsuccessful Mars missions were attempted by the USSR and then NASA. Then, in 1964, history was made when NASA launched the Mariner 4 and completed the first-ever successful trip to Mars.
The Mariner 4 didn’t actually land on the planet, but the spacecraft flew by Mars and was able to capture photos, which gave us an up-close glimpse at the planet’s rocky surface.
Then on July 20, 1976, NASA made history again when its spacecraft called Viking 1 touched down on Mars’ surface, making it the first space agency to complete a successful Mars landing. Viking 1 captured panoramic images of the planet’s terrain, and also enabled scientists to monitor the planet’s weather.
Vacation to Mars, Anyone?
To date, all Mars landings have been done without crews, but NASA is planning to send humans to Mars by the late 2030s.
And it’s not just government agencies that are planning missions to Mars—a number of private companies are getting involved, too. Elon Musk’s aerospace company SpaceX has a long-term plan to build an entire city on Mars.
Two other aerospace startups, Impulse and Relativity, also announced an unmanned joint mission to Mars in July 2022, with hopes it could be ready as soon as 2024.
As more players are added to the mix, the pressure is on to be the first company or agency to truly make it to Mars. If (or when) we reach that point, what’s next is anyone’s guess.
Thematic Investing: 3 Key Trends in Cybersecurity
Cyberattacks are becoming more frequent and sophisticated. Here’s what investors need to know about the future of cybersecurity.
Thematic Investing: 3 Key Trends in Cybersecurity
In 2020, the global cost of cybercrime was estimated to be around $945 billion, according to McAfee.
It’s likely even higher today, as multiple sources have recorded an increase in the frequency and sophistication of cyberattacks during the pandemic.
In this infographic from Global X ETFs, we highlight three major trends that are shaping the future of the cybersecurity industry that investors need to know.
Trend 1: Increasing Costs
Research from IBM determined that the average data breach cost businesses $4.2 million in 2021, up from $3.6 million in 2017. The following table breaks this figure into four components:
|Cost Component||Value ($)|
|Cost of lost business||$1.6M|
|Detection and escalation||$1.2M|
|Post breach response||$1.1M|
The greatest cost of a data breach is lost business, which results from system downtimes, reputational losses, and lost customers. Second is detection and escalation, including investigative activities, audit services, and communications to stakeholders.
Post breach response includes costs such as legal expenditures, issuing new accounts or credit cards (in the case of financial institutions), and other monitoring services. Lastly, notification refers to the cost of notifying regulators, stakeholders, and other third parties.
To stay ahead of these rising costs, businesses are placing more emphasis on cybersecurity. For example, Microsoft announced in September 2021 that it would quadruple its cybersecurity investments to $20 billion over the next five years.
Trend 2: Remote Work Opens New Vulnerabilities
According to IBM, companies that rely more on remote work experience greater losses from data breaches. For companies where 81 to 100% of employees were remote, the average cost of a data breach was $5.5 million (2021). This dropped to $3.7 million for companies that had under 10% of employees working from home.
A major reason for this gap is that work-from-home setups are typically less secure. Phishing attacks surged in 2021, taking advantage of the fact that many employees access corporate systems through their personal devices.
|Type of Attack||Number of attacks in 2020||Number of attacks in 2021||Growth (%)|
As detected by Trend Micro’s Cloud App Security.
Spam phishing refers to “fake” emails that trick users by impersonating company management. They can include malicious links that download ransomware onto the users device. Credential phishing is similar in concept, though the goal is to steal a person’s account credentials.
A tactic you may have seen before is the Amazon scam, where senders impersonate Amazon and convince users to update their payment methods. This strategy could also be used to gain access to a company’s internal systems.
Trend 3: AI Can Reduce the Cost of a Data Breach
AI-based cybersecurity can detect and respond to cyberattacks without any human intervention. When fully deployed, IBM measured a 20% reduction in the time it takes to identify and contain a breach. It also resulted in cost savings upwards of 60%.
A prominent user of AI-based cybersecurity is Google, which uses machine learning to detect phishing attacks within Gmail.
Machine learning helps Gmail block spam and phishing messages from showing up in your inbox with over 99.9% accuracy. This is huge, given that 50-70% of messages that Gmail receives are spam.
– Andy Wen, Google
As cybercrime escalates, Acumen Research and Consulting believes the market for AI-based security solutions will reach $134 billion by 2030, up from $15 billion in 2021.
Introducing the Global X Cybersecurity ETF
The Global X Cybersecurity ETF (Ticker: BUG) seeks to provide investment results that correspond generally to the price and yield performance, before fees and expenses, of the Indxx Cybersecurity Index. See below for industry and country-level breakdowns, as of June 2022.
|Sector (By security type)||Weight|
|🇰🇷 South Korea||0.9%|
Totals may not equal 100% due to rounding.
Investors can use this passively managed solution to gain exposure to the rising adoption of cybersecurity technologies.
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