Revolutionizing Manufacturing with High-Performance Computing and Supercomputers

Exploring the benefits of combining HPC, supercomputers, robotics and automation to drive efficiency and innovation in manufacturing.

Oak Ridge National Laboratory Manufacturing Demonstration Facility. (Source: ORNL.)

Oak Ridge National Laboratory Manufacturing Demonstration Facility. (Source: ORNL.)

Producing products quickly, efficiently and at low cost is a focal point for the manufacturing sector. There are a number of technologies that companies are using to achieve those goals including high performance computing (HPC) and supercomputing. The allure of cheap design and production optimization is strong, but a central barrier is the upfront costs of an enterprise owning an HPC or supercomputing machine.

That’s why in 2021, The U.S. Department of Energy began providing companies with HPC access via the High Performance Computing for Energy Innovation program. In addition to providing funding opportunities, the program allows companies to partner with national laboratories that have advanced computing resources up to 100 times more powerful than typical enterprise systems available for private sector use.

HPC and supercomputing technologies could usher in a manufacturing revolution marked by faster product development, improved product quality, reduced costs and increased efficiency.


Ideas sometimes work better in theory than in practice. Being able to visualize how a part or product will behave in the real world prior to the production process can save design teams a lot of headaches.

HPC and supercomputing technologies enable manufacturers to simulate and model products and production processes at a scale that was previously impossible. This allows manufacturers to design better products and optimize manufacturing processes. For example, in the automotive industry, manufacturers use HPC to simulate vehicle crashes and predict the behavior of materials under extreme conditions, which helps in designing safer and more durable vehicles.

A recent example is Tesla building its custom Dojo supercomputer to expand neural net training capacity using video data to advance computer vision technology to make self-driving vehicles safer.

In the aerospace industry, manufacturers use HPC to simulate how certain aircraft components will perform under varying conditions. Such simulations help manufacturers design more fuel efficient and reliable aircraft. For the semiconductor industry, HPC can help optimize performance through design simulation. Even complex systems such as cross-regional transportation networks can benefit from HPC simulation.

Design simulation is a primary area where HPC and supercomputers can help the manufacturing process. However, advanced simulation technologies have other uses during production and post-production.

Once products and systems are up and running, they need to be maintained. Simulation technologies can help pinpoint what maintenance needs to be performed in order to prevent equipment failures, which can be costly.

HPC and supercomputing simulations can help optimize the production process by helping manufacturers identify bottlenecks and efficiencies. For example, in the chemical industry, manufacturers use simulation and modeling technology to optimize the production process for chemicals such as polymers and plastics. This enables them to reduce the amount of raw materials and energy required to produce a given amount of product, resulting in significant cost savings. Similarly, advanced simulation technologies can help manufacturers like automakers simulate the performance of systems such as brakes under stressful, real-world-like conditions to correct any defects or deficiencies that the models identify.

In high-risk factory conditions, advanced simulations can also help train employees on equipment and tasks prior to their doing so in a real production environment. This can help reduce the risk of accidents while also enhancing worker productivity.

Fast-track time-to-market

Getting products to market as fast as possible is a top concern for manufacturers. HPC and supercomputers can help companies stay ahead of the competition. For example, in the pharmaceutical industry, they can accelerate drug discovery by simulating the behavior of molecules and predicting their effectiveness at targeting diseases. This helps quicken the pace that drugs can move to clinical trials and ultimately enter the market.

Several studies and case studies demonstrate the benefits of using HPC and supercomputers to accelerate product development in manufacturing.  A study conducted by the Council on Competitiveness found that the use of HPC and supercomputers in product design and development can reduce product development time and reduce the number of physical prototypes needed.

The U.S. Department of Energy’s (DOE) High Performance Computing for Manufacturing program has funded several projects that demonstrate the benefits of using HPC and supercomputers in manufacturing. The Partnership for Advanced Computing in Europe (PRACE) has also funded several projects in the same vein.

Hewlett Packard Enterprise has made its HPE Cray portfolio available to the enterprise. The new HPE Cray EX and HPE Cray XD supercomputers speed up time-to-insight with massive performance and AI-at-scale benefits, delivered in a smaller data center footprint and at a lower price point. This allows manufacturers and other industries to harness insights, solve problems and innovate faster by delivering energy-efficient supercomputers in a smaller form factor and at a lower cost.

The simulation and modeling power of HPC and supercomputers helps reduce manufacturing costs by enabling the avoidance of errors during prototyping, reducing the time and resources needed for design and development and optimizing the supply chain.

The Council on Competitiveness found that using HPC and supercomputers can reduce design and development costs. By optimizing designs through simulation and modeling, manufacturers can avoid costly mistakes that may arise during physical prototyping and testing.

The Oak Ridge National Laboratory (ORNL) is helping manufacturers by developing innovative approaches to using its Spallation Neutron Source (SNS) supercomputer and the High Flux Isotope Reactor (HFIR) to allow researchers to examine microstructures to better design new materials and fabrication methods, and leverage multidisciplinary expertise for the development of new bio-based materials. These efforts are geared toward driving economic competitiveness, energy efficiency and productivity.

Enhance automation

HPC and supercomputing systems are also being combined with robotics and automation to enhance manufacturing.

The technologies can analyze real-time data from sensors in factory environments so that robots can use the insights to adapt to changing conditions while maintaining accuracy and efficiency. The data analysis can also be used to optimize robotic systems for greater performance and efficiency. HPC and supercomputers can be used for virtual commissioning, allowing manufacturers to test and optimize robotic systems in a virtual environment before they are deployed in the real world. Supercomputers are also used to train and deploy machine learning models that can direct robots and autonomous systems to make more precise movements and decisions without human intervention.

A number of companies are using this approach, including GE, who has developed a software platform called Predix that combines HPC and supercomputers with the Internet of Things (IoT) to optimize the performance of its manufacturing equipment. This has helped to reduce downtime and improve overall efficiency. Siemens is using HPC and supercomputers to develop virtual commissioning tools such as the Tecnomatix Process Simulate Commissioning and Tecnomatix Plant Simulation Commissioning, which enable manufacturers to test and optimize robotic systems in a virtual environment.

The manufacturing sector is poised for a revolution driven by HPC, supercomputers and AI. Part of that will likely involve the advancement of quantum computing, which has applications for the manufacturing sector as well. Because quantum computers make simultaneous calculations versus the sequential calculations of classical machines, they could enable factory robots to move with greater efficiency and precision, driving better throughput for more complicated tasks. Quantum computers could also advance the creation of new materials for use as semiconductors, industrial production catalysts, electronic components, sustainable fuels, pharmaceuticals and consumer products. As these technologies continue to evolve, it is likely that we will see even more advanced and innovative applications in the manufacturing sector.

This story is one in a series underwritten by AMD and produced independently by the editors of Subscribe here to receive informative infographics, handy fact sheets, technology recommendations and more in AMD’s data center insights newsletter.