The world of computing is on the brink of a revolutionary change with the advent of supercomputing. This exciting field of computer science and engineering is pushing the boundaries of what machines can do, with several countries racing to develop the most powerful supercomputers. Unlike your everyday laptop, these supercomputers can occupy entire buildings and are designed to tackle some of the most complex problems facing humanity today.
At first glance, supercomputers might remind you of the early days of computing, like the ENIAC, the first programmable digital computer. The ENIAC could perform about 400 floating-point operations per second (FLOPS), a measure of computing power. This was a groundbreaking achievement in 1945, as it performed more calculations in its decade of operation than humanity had done up to that point.
Since then, computing power has skyrocketed from 400 FLOPS to petascale levels, reaching quadrillions of operations per second. Now, we’re on the cusp of exascale computing, capable of performing 1 quintillion operations per second. To put this into perspective, achieving the same number of calculations manually would take over 31 billion years!
Why do we need such immense computing power? Exascale computers will help us simulate and understand large-scale phenomena like climate change, which involves countless variables and complex interactions. On a smaller scale, they will model molecular interactions between cells and drugs, providing insights into disease mechanisms and potential treatments.
Exascale computing will enhance our capabilities in fields ranging from chemistry and genetics to aircraft design and nuclear physics. It will also aid in energy grid planning, offering unprecedented power, speed, specificity, and accuracy.
However, this leap in performance comes with significant costs. Exascale systems are expensive, costing hundreds of millions of dollars, and they consume vast amounts of electricity. Cooling these powerful machines requires additional energy, as they generate substantial heat during operation.
Moreover, exascale computers will require a new approach to connecting processors, memory, and storage, all of which must handle unprecedented amounts of information. This means rethinking the physical architecture of these machines and developing new software to communicate effectively with them.
The United States is in a fierce competition to achieve exascale computing first. The Frontier supercomputer, expected to come online at Oak Ridge National Lab, aims to reach 1.5 exaflops. Following closely is El Capitan at Lawrence Livermore National Lab, projected to achieve 2 exaflops by 2023. However, China is also making significant strides, with three exascale machines in development, potentially surpassing the U.S.
While the U.S. and China lead the race, other countries, including Japan and several European nations, are also working on exascale projects.
Building the hardware is just the beginning. To harness the full potential of exascale computing, software engineers play a crucial role in developing the necessary programs and applications. This is an exciting time for those in the field, as they contribute to solving some of the world’s most complex scientific challenges.
For more insights into cutting-edge computing innovations, explore topics like quantum computing chips. Stay tuned for more updates on the world of computing, and feel free to share your thoughts and questions in the comments. Don’t forget to subscribe to Seeker for the latest in technology and science. Thank you for joining us on this journey, and see you next time!
Explore the evolution of supercomputers by researching a specific historical supercomputer, such as the ENIAC or Cray-1. Prepare a short presentation to share with your classmates, highlighting its significance, technological advancements, and impact on the field of computing.
Engage in a hands-on project where you use high-performance computing resources to simulate a complex problem, such as climate modeling or molecular interactions. Document your process and findings, and discuss the challenges and benefits of using supercomputing for such tasks.
Participate in a structured debate on the ethical considerations surrounding exascale computing. Topics can include the environmental impact, cost versus benefit, and global competition. Prepare arguments for both sides and engage in a lively discussion with your peers.
Work in groups to design a conceptual model of an exascale computer. Consider aspects such as processor architecture, cooling systems, and energy efficiency. Present your model to the class, explaining the rationale behind your design choices and how they address the challenges of exascale computing.
Conduct an interview with a software engineer who works with high-performance computing systems. Prepare questions about their role, the challenges they face, and the future of software development in the context of exascale computing. Share your insights and reflections with the class.
The next generation of computing is on the horizon, and it is super. This field of computer science and engineering is called supercomputing, and several new machines may just break all the records, with two nations neck and neck in a race to see who will get there first. Supercomputers are quite different from something like your laptop. They can take up whole buildings and are used to solve some of the most complicated problems in the world.
Just by looking at them, they may not seem that different from a machine like the ENIAC, the first ever programmable digital computer. The ENIAC was capable of about 400 FLOPS, which stands for floating-point operations per second, indicating how many calculations the computer can perform in a second. This makes measuring FLOPS a way of calculating computing power. The ENIAC was sitting at 400 FLOPS in 1945, and in the ten years it was operational, it may have performed more calculations than all of humanity had up until that point in time—that was the kind of leap digital computing gave us.
From that 400 FLOPS, we upgraded to 10,000 FLOPS, then a million, a billion, a trillion, and a quadrillion FLOPS. That’s petascale computing, which is the level of today’s most powerful supercomputers. But what’s coming next is exascale computing, which is 1 quintillion operations per second. Exascale computers will be a thousand times better performing than the petascale machines we have now. To put it another way, if you wanted to do the same number of calculations that an exascale computer can do in one second, you’d be doing math for over 31 billion years.
So, what do we need that kind of computing power for? Large-scale phenomena like climate change have so many moving parts that are all affected by minute changes in other variables, and the effects of these changes need to be projected forward in time. That’s a really complex situation to simulate. On the other end of the spectrum, molecular interactions between cells and drug compounds are also extremely complex—just on the nanoscale—and computer models of these interactions allow us to see the actual mechanisms of how diseases affect us and how different medicines could interrupt those interactions.
Exascale computing will provide us with more power, speed, specificity, and accuracy than we’ve ever had before. It’ll be like looking at the world through a new pair of prescription glasses, bringing into sharper focus everything from chemistry to genetics, aircraft design to nuclear physics, even energy grid planning. However, increased performance comes with increased cost. Exascale systems have price tags in the hundreds of millions of dollars, and they require huge amounts of electricity to run.
Just like with humans, running makes computers hot, so computing facilities consume even more energy (and cold water) to cool the computers down and keep them at optimum performance. Computers that are unrivaled in their power are also unrivaled in their complexity. Exascale machines will, for lack of a better word, ‘think’ differently than their predecessors. We’re going to need to connect their processors in a different way. Not only that, but exascale processors have to connect to memory and storage in a different way too—and both of these will have to contain unprecedented amounts of information.
From the software side, you essentially have to ‘talk’ to these computers in a different way than you do to petascale machines. So, if you want to take codes that were designed to run on petascale computers and run them on an exascale machine, you need to do some major code overhaul. This all means that the dawn of exascale requires huge innovations in everything from the physical architecture of the hardware to software programming to engineering the buildings these computers will inhabit.
When can we expect to see these mega machines? The first exascale machine in the U.S. was slated to arrive at Argonne National Lab sometime in 2021, but has been delayed. That supercomputer is called Aurora, and its team plans to use Intel GPU computer chips—the slow development of which seems to be holding things up. The machine that was supposed to come online second has now moved into first place. That’s the Frontier supercomputer, which may come online this year at Oak Ridge National Lab and will clock in at 1.5 exaflops. In 2023, Frontier will be followed by El Capitan at Lawrence Livermore National Lab, a machine capable of 2 exaflops.
That’s a significant amount of power. However, it remains to be seen if the U.S. will actually achieve exascale computing first, as China is also bringing three new exascale machines into the spotlight and may very well get there before anyone else. Even though the U.S. and China are leading the pack, many other countries, from Japan to various places in Europe, also have exascale machines in the works.
The machine hardware itself is really just the skeleton of exascale computing. To actually bring that maximum power to bear on some of the most complex problems scientists are trying to untangle today, there’s a lot more going on behind the scenes. So, software engineers—now’s your time to shine. If you want more on boundary-breaking computing innovations, check out our video on quantum computing chips. If you have other computational news you want us to cover, let us know in the comments below. Make sure you subscribe to Seeker for all your coverage of bits and bytes, and as always, thanks for watching. See you in the next one.
Computing – The process of utilizing computer technology to complete a given goal-oriented task. – Computing has revolutionized the way we analyze large datasets in scientific research.
Supercomputers – Extremely fast computers that can perform hundreds of millions of instructions per second, used for complex simulations and calculations. – Supercomputers are essential for climate modeling and predicting weather patterns.
Exascale – Referring to computing systems capable of at least one exaflop, or a billion billion calculations per second. – The development of exascale computing is crucial for advancing artificial intelligence applications.
Performance – The efficiency and speed with which a computer or software program operates. – Optimizing the performance of a database system can significantly reduce query response times.
Architecture – The conceptual structure and logical organization of a computer or computer-based system. – Understanding computer architecture is fundamental for designing efficient hardware systems.
Software – Programs and other operating information used by a computer. – Developing robust software is key to ensuring the reliability of automated systems.
Engineers – Professionals who apply scientific knowledge to design, build, and maintain structures, systems, and devices. – Engineers play a critical role in the advancement of renewable energy technologies.
Electricity – A form of energy resulting from the existence of charged particles, used to power computers and other devices. – Efficient electricity management is vital for data centers to reduce operational costs.
Simulations – The imitation of a real-world process or system over time, often used in engineering and computing to test scenarios. – Simulations are used in engineering to predict the behavior of structures under stress.
Technology – The application of scientific knowledge for practical purposes, especially in industry. – Advances in technology have led to the development of more powerful and compact computing devices.
