What is a Supercomputer? Features, Importance, and Examples

A supercomputer processes data at lightning speeds, measured in floating-point operations per second (FLOPS).

Last Updated: December 1, 2022

A supercomputer is defined as an extremely powerful computing device that processes data at speeds measured in floating-point operations per second (FLOPS) to perform complex calculations and simulations, usually in the field of research, artificial intelligence, and big data computing. This article discusses the features, importance, and examples of supercomputers and their use in research and development.

What Is A Supercomputer?

A supercomputer is an extremely robust computing device that processes data at speeds measured in floating-point operations per second (FLOPS) to perform complex calculations and simulations, usually in the field of research, artificial intelligence, and big data computing. 

Supercomputers operate at the maximum rate of operation or the best performance rate for computing. The primary distinction between supercomputers and basic computing systems is processing power. 

A supercomputer could perform computations at 100 PFLOPS. A standard general-purpose computer is limited to scores of gigaflops to tens of teraflops in processing speed. Supercomputers consume huge amounts of energy. Consequently, they produce so much heat that users must retain them in cooling environments.

Evolution of supercomputers

In the early 1960s, IBM introduced the IBM 7030 Stretch, and Sperry Rand introduced the UNIVAC LARC, the first two supercomputers intentionally built to be significantly more powerful when compared to the quickest business machines available at the time. In the late 1950s, the U.S. government consistently supported the research and creation of state-of-the-art, high-performing computer technology for defense purposes, influencing supercomputing development.

Although only a small number of supercomputers were initially manufactured for government use, the new technology would eventually enter the commercial and industrial sectors, mainstreaming the technology. For instance, from the mid-1960s until the late 1970s, Control Data Corporation (CDC) and Cray Research dominated the commercial supercomputer sector. Seymour Cray’s CDC 6600 is regarded as the first commercially viable supercomputer. IBM would become a market leader from the 1990s onwards and right to the present day.

How do supercomputers work?

The architectures of supercomputers consist of many central processor units (CPUs). These CPUs are organized into clusters of computation nodes and memory storage. Supercomputers may have many nodes linked to solve problems via parallel processing.

Multiple concurrent processors which conduct parallel processing comprise the biggest and most powerful supercomputers. Two parallel processing methodologies exist: symmetric multiprocessing and massively parallel processing. In other instances, supercomputers are dispersed, meaning they take power from many PCs located in several areas instead of putting all CPUs in a single location.

Supercomputers are measured in floating point operations per second or FLOPS, whereas previous systems were generally measured in IPS (instructions per second). The greater this value, the more effective the supercomputer.

In contrast to conventional computers, supercomputers have many CPUs. These CPUs are organized into compute nodes, each having a processor or group of processors – symmetric multiprocessing (SMP) — and a memory block. A supercomputer may comprise a large number of nodes at scale. These nodes may work together to solve a particular issue using interconnect communications networks.

Notably, due to the power consumption of current supercomputers, data centers need cooling systems and adequate facilities to accommodate all of this equipment.

Types of supercomputers

Supercomputers may be divided into the following classes and types:

  • Tightly connected clusters: These are groupings of interconnected computers that collaborate to solve a shared challenge. There are four approaches to establishing clusters for connecting these computers. This results in four cluster types: two-node clusters, multi-node clusters, director-based clusters, and massively parallel clusters.
  • Supercomputers with vector processors: This occurs when the CPU can process a full array of data items simultaneously instead of working on each piece individually. This offers a sort of parallelism in which all array members are processed simultaneously. Such supercomputer processors are stacked in arrays that can simultaneously process many data items.
  • Special-purpose computers: These are intended for a particular function and can’t be used for anything else. They are meant to address a specific problem. These systems devote their attention and resources to resolving the given challenge. The IBM Deep Blue chess-playing supercomputer is an example of a supercomputer developed for a specific task.
  • Commodity supercomputers: These consists of standard (common) personal computers linked by high-bandwidth, fast Local Area Networks (LANs). These computers then use parallel computing, working together to complete a single task.
  • Virtual supercomputers: A virtual supercomputer essentially works on, and lives in the cloud. It offers a highly efficient computing platform by merging many virtual machines on processors in a cloud data center.

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Features Of A Supercomputer

Standard supercomputer features include the following:

1. High-speed operations, measured in FLOPS

Every second, supercomputers perform billions of computations. As a performance metric, these use Floating-Point Operations per Second (FLOPS). A FLOPS measures the number of fluctuating computations a CPU can perform every second. Since the vast majority of supercomputers are employed primarily for scientific research, which demands the reliability of floating numbers, FLOPS are recommended when evaluating supercomputers. The performance of the fastest supercomputers is measured in exaFLOPS.

2. An extremely powerful main memory

Supercomputers are distinguished by their sizeable primary memory capacity. The system comprises many nodes, each with its own memory addresses that may amount to approximately several petabytes of RAM. The frontier, the world’s fastest computer, contains roughly 9.2 petabytes of storage or memory. Even other supercomputers have a considerable RAM capacity.

3. The use of parallel processing and Linux operating systems

Parallel processing is a method in which many processors work concurrently to accomplish a specific computation. Each processor is responsible for a portion of the computation to solve the issue as quickly as practicable. In addition, most supercomputers use modified versions of the Linux operating system. Operating systems based on Linux are used because they are publicly available, open-source software, and execute instructions more efficiently.

4. Problem resolution with a high degree of accuracy

With the vast volume of data constantly processed and its accelerated execution, there is a possibility that the computer may provide inaccurate results at any point. It has been shown that supercomputers are accurate in all their calculations and provide correct information. With faster and more precise simulations, supercomputers can effectively tackle problems. Supercomputers are assigned several repetitions of a problem, which they answer in a split second. These iterations are also capable of being created by supercomputers. Supercomputers can accurately answer any numerical or logical issue.

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Why Are Supercomputers Important?

Today, the world is increasingly dependent on supercomputers for the following reasons:

1. Supporting artificial intelligence research (AI) initiatives 

Artificial intelligence (AI) systems often demand efficiency and processing power equivalent to that of a supercomputer. Machine-learning and artificial intelligence app developments consume massive volumes of data, which supercomputers can manage.

Some supercomputers are designed with artificial intelligence in consideration. Microsoft, for instance, custom-built a supercomputer for training huge AI models that are compatible with it’s Azure cloud platform. The objective is to deliver supercomputing resources to programmers, data analysts, and business customers via Microsoft Azure’s AI services. Microsoft’s Turing Natural Language Generation is one such tool; it is a natural language processing framework. Nvidia’s Perlmutter is yet another instance of a supercomputer designed exclusively for AI tasks.

2. Simulating mathematical problems to invest in the right direction

Because supercomputers can calculate and predict particle interactions, they have become an indispensable tool for researchers. In a way, interactions are occurring everywhere. This includes the weather, the formation of stars, and the interaction of human cells with drugs.

A supercomputer is capable of simulating all of these interactions. Scientists may then use the data to gain valuable insights, such as whether it will snow tomorrow, whether a new scientific hypothesis is legitimate, or if an impending cancer therapy is viable. The same technology may also enable enterprises to examine radical innovations and choose which ones merit real-world verification or testing.

3. Using parallel processing to solve complex problems

Decades ago, supercomputers began using a technique known as “massively parallel processing,” in which problems were divided into sections and worked on concurrently by thousands of processors instead of the “serial” approach. 

Comparable to arriving at the register with a full shopping cart and then dividing the items among numerous companions. Each “friend or companion” may proceed to a separate checkout and pay individually for a couple of the products. After everyone has paid, they may reunite, reload the cart, and exit the store. The greater the number of articles and friends, the quicker parallel processing gets.

4. Predicting the future with an increasing level of accuracy

Large-scale weather forecast models and the computers that operate them have progressively improved over the past three decades, resulting in more exact and reliable hurricane path predictions. Supercomputers have contributed to these advancements in forecasting when, where, and how extreme storms may occur. Additionally, users may extend the same ideas to other historical occurrences. 

Is it surprising that supercomputers are being prepared and trained to anticipate wars, uprisings, and other societal disruptions in this era of big data?

Kalev Leetaru, a Yahoo Fellow-in-Residence at Georgetown University, Washington, D.C., has accumulated a library of over one hundred million articles from media sources throughout the globe, spanning thirty years, with each story translated and categorized for geographical region and tone. Leetaru processed the data using the shared-memory supercomputer Nautilus, establishing a network of 10 billion objects linked by 100 trillion semantic links.

This three-decade-long worldwide news repository was part of the Culturomics 2.0 project, which forecasted large-scale human behavior by analyzing the tone of global news media as per timeframe and location.

5. Identifying cyber threats at lightning speed

Identifying cybersecurity risks from raw internet data may be comparable to searching for a needle in a pile of hay. For instance, the quantity of web traffic data created in 48 hours is just too large for a single laptop or even 100 computers to convert into a form human analysts can comprehend. For this reason, cybersecurity analysts depend on sampling to identify potential dangers.

Supercomputing may provide a more advanced solution. In a newly published research titled “Hyperscaling Internet Graph Analysis with D4M on the MIT SuperCloud,” a supercomputer successfully compressed 96 hours of unprocessed, 1-gigabit network-linked internet traffic information into a query-ready bundle. It constructed this bundle using 30,000 computing cores (at par with 1,000 personal computers).

6. Powering scientific breakthroughs across industries 

Throughout its history, supercomputing has been of considerable significance because it has enabled significant improvements in vital sectors of national security and scientific discovery, and the resolution of societally significant issues.

Currently, supercomputing is utilized to solve complex issues in stockpile management, military intelligence, meteorological prediction, seismic modeling, transportation, manufacturing, community safety and health, and practically every other field of fundamental scientific study. The significance of supercomputing in these fields is growing, and supercomputing is showing an ever-increasing influence on future advancements.

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Examples of Supercomputers

Now that we have discussed the meaning of supercomputers and how the technology works let us look at a few real-world examples. Here are the most notable examples of supercomputers you need to know:

1. AI Research SuperCluster (RSC) by Facebook parent Meta

Facebook’s parent company, Meta, said in January 2022 that it would develop a supercomputer slated to be among the world’s most powerful to increase its data processing capability. Its array of devices could process videos and images up to 20 times quicker than their present systems. Meta RSC is anticipated to assist the organization in developing unique AI systems that may, for instance, enable real-time speech translations for big groups of individuals who speak various languages.

2. Google Sycamore, a supercomputer using quantum processing

Google AI Quantum created the quantum computer Google Sycamore. The Google Sycamore chip is based on superconducting qubits, a type of quantum computing that combines superconducting materials and electric currents to store and manage information. With 54 qubits, the Google Sycamore chip can perform a computation in 200 seconds which would take a traditional processor 10,000 years to finish.

3. Summit, a supercomputer by IBM

Summit, or OLCF-4, is a 200 petaFLOPS-capable supercomputer designed at IBM for deployment at the Oak Ridge Leadership Computing Facility (OLCF). As of November 2019, the supercomputer’s estimated power efficacy of 14.668 gigaFLOPS/watt ranked it as the fifth most energy-efficient in the world. The Summit supercomputer allows scientists and researchers to address challenging problems in energy, intelligent systems, human health, and other study sectors. It has been used in modeling earthquakes, material science, genetics, and the forecasting of neutrino lifetimes in physics.

4. Microsoft’s cloud supercomputer for OpenAI

Microsoft has constructed one of the world’s top five publicly reported supercomputers, making new OpenAI technology accessible on Azure. It will aid in the training of massive artificial intelligence models. This is a critical step toward establishing a platform upon which other organizations and developers may innovate. The OpenAI supercomputer is a single system with around 285,000 CPU cores, 10,000 GPUs, and 400 gigabits every second of network bandwidth per GPU server.

5. Fugaku by Fujitsu

Fujitsu placed Fugaku in the RIKEN Center for Computational Science (R-CCS) in Japan’s Kobe prefecture. The system’s upgraded hardware set a new worldwide record — 442 petaflops. Its only mission is to address the world’s most pressing problems, with a particular emphasis on climate change. The most significant difficulty for Fugaku is correctly anticipating global warming depending on carbon dioxide emissions and their effect on the population worldwide.

6. Lonestar6 by the Texas Advanced Computing Center (TACC) at the University of Texas

Lonestar6 is certified at three petaFLOPS, which indicates that it is capable of about three quadrillion calculations per second. TACC says that to replicate what Lonestar6 can calculate in one second, humans must do one computation every moment for 100 million years. It is a hybrid structure comprising air-cooled and liquid (oil) immersion-cooled components. And over 800 Dell EMC PowerEdge C6525 servers function as a single HPC system. Lonestar6 supports the initiatives of the University of Texas Research Cyberinfrastructure, such as COVID-19 studies and drug development, hurricane modeling, wind energy, and research on dark energy.

7. Qian Shi, Baidu’s quantum supercomputer

This year, Baidu, Inc. unveiled its first-ever superconducting quantum computer, which combines technology, algorithms, software, basic hardware, and apps. Atop this infrastructure sits several quantum applications, including quantum algorithms deployed to create new materials for revolutionary lithium batteries or emulate protein folding. Qian Shi provides the general public with a ten-qubit quantum computing service that is both secure and substantial.

8. Virtual supercomputing by AWS

In 2011, Amazon constructed a virtualized supercomputer on top of its Elastic Compute Cloud (EC2), a web service that creates virtual computers on demand. The nonexistent (i.e., virtual) supercomputer was faster than all but 41 of the world’s actual supercomputers at the time. EC2 by Amazon Web Services (AWS) is capable of competing with supercomputers constructed using standard microprocessors and commodity hardware components.

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Takeaway

Supercomputers have evolved in leaps and bounds from costly and bulky systems. For example, HPE revealed its new supercomputer at Supercomputing 2022 (SE22), which is not only powerful but also energy efficient. The rapid proliferation of data also means that supercomputing technology now has more information to ingest and can create better models and simulations. Eventually, organizations and individuals will be able to use hardware and cloud-based resources to build bespoke supercomputing setups.

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Chiradeep BasuMallick
Chiradeep is a content marketing professional, a startup incubator, and a tech journalism specialist. He has over 11 years of experience in mainline advertising, marketing communications, corporate communications, and content marketing. He has worked with a number of global majors and Indian MNCs, and currently manages his content marketing startup based out of Kolkata, India. He writes extensively on areas such as IT, BFSI, healthcare, manufacturing, hospitality, and financial analysis & stock markets. He studied literature, has a degree in public relations and is an independent contributor for several leading publications.
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