Real-time market intelligence, human anatomical modeling, predictive industrial exploration, space science, and many more human expeditions drive the current world into an unimaginable future, due in no small part to high-performance computing (HPC).
Despite requiring enormous resources, high-performance computing programs keep rolling out, thanks to the invention of supercomputers and widespread implementation of cloud computing. These technologies make life easy, supporting unfathomable rapid data processing.
Some applications of HPC are redesigning how science will serve you in the future. But first, what’s high-performance computing?
What Is High-Performance Computing?
High-performance computing refers to the capacity of a system to process an enormous amount of data and run complex models rapidly. HPC programs, therefore, require a huge compute power to process terabytes, petabytes, or even zettabytes of data in real-time.
Thus, HPC relies on the principle of computing, networking, and data storage.
That said, here are some notable applications of high-performance technology that have influenced the world.
1. Predictive Cardiovascular Health
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No doubt, heart failure is life-threatening. And perhaps one of the challenges faced while trying to understand its mechanisms is the differences in the anatomical response of the heart to various conditions. Consequently, it becomes difficult to predict its behavior in real-time.
Thankfully, some HPC-based solutions are coming up.
For instance, IBM, along with a defense laboratory, historically simulated the homeostatic mechanisms of the human heart on a molecular level using one of the world’s fastest supercomputers, Sequoia, in 2012.
They leveraged Sequioa’s high-computing speed to build a scalable model called “Cardioid” to mimic and rebuild the human heart. And unlike previous programs that could only simulate about ten heartbeats or lower, the Cardioid program could mimic thousands of heartbeats. Plus, it was 300 times faster than most models.
IBM’s Cardioid project isn’t the only high-performance computing program revolutionizing cardiac health, Dassault Systemes’ Living Heart Project is also a notable one.
Thus, you can expect to see drugs and various regimens tested on a simulated heart first before being administered to humans. These HPC programs also promise to improve cardiovascular devices and organ placement during surgeries.
In 2018, Google also developed a deep learning model that predicts cardiovascular disease risks using computer vision from scanned retina images.
The technology works by assessing the eye blood vessels and then using this to predict systolic blood pressure and identify other risk pointers.
Such a program aids early detection of cardiovascular problems, which is a key to their prevention.
That said, simulated electrocardiogram (ECG) AI models are also springing up to aid effective diagnosis for people with ventricular anomalies. Consequently, while open-heart surgeries are becoming more successful, the world is drifting towards an era where patients and doctors are more confident about the outcome of heart surgeries than ever before.
One successful application of cardiovascular modeling is the report by CNN health of the 3D simulation of a 4-year-old girl’s heart at Nicklaus Children Hospital in 2015. That’s phenomenal, as surgeons were able to operate a simulated version of the patient’s heart and envisage the best operational procedures before the actual surgery.
2. Understanding the Viral Genome
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Although the viral genome could be sequenced, understanding its invasive pathology in real-time is difficult as it mutates. But thanks to high-performance computing, ground-breaking simulations of these mechanisms are evolving. And it’s helping decision-makers.
A more recent example of a high-performance computing application, in this case, is CSIRO’s exploration of the COVID-19 complete genome, which they simulated on a CSIRO supercomputer in early 2020.
The CSIRO Data61 team successfully simulated the binding mechanism of COVID-19 to the human ACE2 receptor.
COVID-19 is an actively mutating virus. But a simulation of its mechanism of action goes a long way to help researchers understand most of its evolving behaviors. Such a breakthrough doesn’t only help scientists to know where a vaccine should target on a COVID-19 viral genome. But it’s also a template for the development of a predictive behavioral pattern for some of the most notorious infectious agents ever known.
Consequently, drug and vaccine development becomes cheaper, faster, and more efficient in combating various infectious agents.
It’s possible that this may help scientists identify human super-genes that could resist infections.
3. Autonomous Driving Technology
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The algorithm required to operate a driverless vehicle is complicated, and it has to process many complex calculations in real-time. Essentially, an autonomous truck or car can’t afford a lag in any of its functionalities. Thus, they need a highly reliable computing speed to run.
Accident simulations, obstacle detection, rapid and accurate response to senses are the key characteristics of driverless vehicles to navigate smartly and safely.
Of course, the purpose of creating self-driving cars is to leverage the accuracy of deep learning to reduce road crashes and accurately predict where to navigate.
Tech and automobile giants, including Tesla, Waymo, Toyota, Honda, Volkswagen, among others, are intensifying their efforts to test driverless cars that comply with public road safety standards.
Many people are skeptical about self-driving cars, though. But this technology, if successfully implemented, will change the face of transportation. And perhaps foster a drive towards a safer road and optimized fuel consumption.
4. Augmented Reality
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With evolving technologies and the advancements in cloud computing, augmented reality, no doubt, will turn fantasies into realism.
Augmented reality can help you choose and test the products that you buy. And it feels like you’re seeing them physically. AR makes it possible to test how products like clothes and accessories look on you before buying them.
It’s even emerging in military operations. An example is Microsoft’s Integrated Visual Augmentation System (IVAS), which helps soldiers see through their entire coordinate in real-time.
In sports, players can even train virtually using VR technology. Virtual reality immersion is also an evolving technology that will foster more realistic visions in the future.
Big tech companies, including Microsoft, Google, among others, have invested in this yielding high-performance computing technology. And with furthter advancements, we think the world will be baffled when TV and gaming become augmented with realistic landscapes and perspectives.
5. NASA’s Solar Weather Monitoring
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NASA, in 2019, leveraged high-performance computing to remotely monitor the extreme ultraviolet irradiating nature of the sun that causes solar flares, the disruptor of solar weather.
The weather condition of the solar system influences the launching of spacecraft, satellites, and solar stations. Therefore, to sustain human exploration in space and protect the earth, it’s necessary to track the changes in solar weather over time.
And of course, a distortion in solar weather can equally affect the earth’s transmitting utilities, especially those that depend on the solar system in one way or another.
NASA uses a dedicated space instrument called EVE MEGS-A to capture the activities of the sun. But stated in its research paper published on Science Advances, that its new deep learning model will fill the gap if EVE MEGS-A malfunctions.
So in conjunction with the Frontier Development Lab, NASA successfully simulated the sun observatory instrument through a deep neural networks model. Because it’s real-time and dynamic, this solution results in rapid decision-making.
That’s a life-changing application of high-performance computing, as it helps astronauts and regulatory agencies to make impactful decisions ahead of an impending disaster.
6. Aircraft Production and Aerodynamics
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High-performance computing is also applicable to manufacturing. Many industries now use this technology to model and predict how undiscovered materials behave. Thus, it creates a gateway to the creation of new industrial materials.
Computational fluid dynamics is one of the areas where HPC has found its purpose. The simulation of wind turbines, aviation parts, and the prediction of the strength of materials has led to the invention of some life-changing products.
AAI, for instance, is an aerospace defense technology organization that models various aero parts based on computational fluid dynamics. AAI’s model, however, focuses on developing HPC-optimized systems for making safer aircraft.
Simulia also developed simulation software using computational fluid dynamics to simulate the dynamic cruise conditions of an aircraft. Simulia and AAI’s solutions reduce production costs and time by eradicating the need for physical testing and the wastage of expensive materials.
The Driving Technologies of High-Performance Computing
Supercomputers and cloud computing are the two major driving forces of HPC programs. They offer space, speed, and scalability.
On-premise supercomputers may be insufficient to catch up with the runtime required by HPC programs as it scales up. And while cloud computing is a scalable and faster alternative, edge computing is an evolving cloud solution that may dominate high-performance computing in the future.
What Are Some Challenges of Writing High-Performance Computing Programs?
The applications of HPC are limitless, and they cut across all aspects of life. So while developing field-specific HPC programs, programmers need to have a vast knowledge about that field. Otherwise, it becomes daunting, as they’re also trying to cope with the technicalities of their code. Another challenge, however, is how to write scalable and implementable code.
That said, high-performance computing will bring more development to the world, even sooner than you might think.