The cloud has made the processing power of the world’s most powerful computers accessible to a wider range of companies than ever before. Instead of having to architect, engineer, and build a supercomputer, companies can now rent hours on the cloud, making it possible bring tremendous computational power to bear on R&D. But where should companies start? What kinds of projects could benefit from this investment? There are a few common uses that have proven value: evaluating new designs through cloud-based simulation instead of physical prototyping, simulating a product’s interaction with real-world scenarios when physically prototyping is impractical, and predicting the performance of a full range of potential designs. It also opens up the possibilities for new products and services, which would have previously been impossible or impractical.
When Is a Supercomputer Worth It?
In the last decade, big data gave the enterprise profound new business insights and improved how large data sets are analyzed. Computational methods in R&D will improve the physical performance of engineered products through simulations just as profoundly. The common thread in all simulations is that we are determining the likely observations of how a product would interact with its environment, based on the scientific principles that shape our world — from physics to chemistry to thermodynamics. Cloud-based supercomputing can be particularly helpful to organizations in the following situations: Accelerate time to market: Evaluating new designs through cloud-based simulation instead of physical prototyping can dramatically accelerate how fast companies are able to commercialize new product innovations. Florida-based startup Sensatek created an innovative IoT sensor that adheres to turbine blades to measure the internal stresses on jet engines during flight. The Air Force wanted to buy Sensatek’s sensors, but the company didn’t have the resources to buy supercomputers to perfect its product fast enough, until it turned to high-performance computing in the cloud. Similarly, Specialized Bicycles performs simulations with rapid prototyping so they can quickly fine tune their road bike aerodynamics and overall performance. Digital twins: Simulating a product’s interaction with real-world scenarios is critical when physically prototyping is impractical. For example, Commonwealth Fusion Systems, a fusion nuclear reactor startup, relies on simulations to validate potential reactor designs, as no commercial fusion reactor has ever existed. Firefly Aerospace, a Texas-based rocket startup, relies on computational engineering to explore and test the designs of its moon-bound commercial rockets. Similarly, drug manufacturers need complex simulations to know how molecules will interact with a biological environment before they can commit to producing new drug discovery breakthroughs. Combine AI/ML with simulation: Simulations can not only predict how a single human-designed product might perform, but it can also predict the performance of a full range of potential designs. Organizations investing in these virtual experiments develop intellectual property on the models covering a broad range of design parameters and implications to product performance. Here is where early-adopter companies gain competitive advantage with their data assets. Automakers like Nissan, Hyundai, and Arrival make it much easier and faster for their engineers to test new design techniques to build safer and more efficient vehicles in an increasingly complex operating environment with autonomous, electric, and connected capabilities. In developing advanced driver assistance systems, ML algorithms can train driver software in simulated worlds. Just as aircraft wind tunnel testing has gone virtual, so can testing for autonomous driving systems. In the life sciences space Recursion Pharmaceuticals is applying Artificial Intelligence techniques to biology, and accelerating new drug discoveries by analyzing cells 20 times faster using machine learning on supercomputers. New computation-enabled products or services: Cloud’s scale and connected nature create new possibilities for science and engineering. For example, Samsung Electronics created a cloud-based platform for computational engineering collaboration, so fabless customers — who design and sell hardware, but don’t manufacture it — can use diverse electronic design automation tools on demand and collaborate on designs with Samsung ahead of manufacturing. This new approach essentially brings continuous integration (a practice common in software development today) to engineered products. Engineers can not only quickly validate their design decisions but also integrate their designs to an overall system for seamless collaboration and systems level simulation and validation.
From Big Data to Big Compute
With all the investments in the past decade around social media, mobile, and cloud technologies, the next major industry transformations are likely to come in the world of science and engineering. In this new world, data generation — not just collection — will grow in importance as simulations that create digital twins of real world products become more common. Harnessing supercomputing in the cloud is becoming foundational to innovation in many industries, particularly as continuous integration and continuous delivery ties R&D ever closer to product cycles and a company’s software delivery process. Supercomputing in the cloud is making possible what seemed like science fiction yesterday. Indeed, there are entire industries that only exist because of this new computational capability — such as private space travel. Rocket companies like SpaceX and Blue Origin were barely possible 15 years ago. These innovation leaders in aerospace required hundreds of millions of dollars just to build the computer infrastructure that could run the simulations their businesses required. But next-generation aerospace companies like Firefly, Relativity and Virgin Orbit can now deliver R&D results at less than a tenth of the cost of their legacy peers. And they can do this today at any scale, rapidly dropping barriers for innovation. Today, anyone can spin up a world-class supercomputer on their credit card. This changes the pace and dynamics of innovation, the impact of which is only recently beginning to emerge.