With the explosion of data and increase in Data Gravity, the key to driving innovation lies in finding faster solutions to complex problems by accessing vast amounts of data. High-performance computing (HPC) offers enterprises an affordable way to harness supercomputing capabilities. Unlike traditional supercomputers, HPC involves clusters of computational nodes connected to extensive storage and bandwidth. This setup allows HPC to efficiently handle even the most intricate scientific, engineering, and AI workloads.
According to Forrester Analytics Business Technographics survey data, there is growing adoption of HPC in both public and private cloud environments among North American and European enterprises. Currently, 30% of infrastructure technology decision-makers in firms using public cloud already run HPC there or plan to do so. 25% of internal private cloud users also have similar intentions. This trend is consistent across various industries, with 33% of respondents in financial services, 29% in media, entertainment, and leisure, and 26% in manufacturing either currently running or planning to implement HPC in public cloud environments.
Factors driving high-performance computing
- The demand for quick solutions to complex problems is driving the mainstream growth of HPC across industries.
- Cloud vendors like AWS, Azure, and Google Cloud are expanding their support for HPC with specialized options, while companies like HPE, IBM, and Penguin Computing offer hybrid cloud and managed services.
- Private cloud options for HPC are on the rise, with vendors providing easy-to-operate infrastructure packages, backed by powerful processors and advisory services.
- Faster networking technologies, particularly remote direct memory access (RDMA) fabrics, enable high-data-throughput applications like AI and ML in public-cloud-based HPC processing, leading to wider adoption of HPC for diverse use cases.
Emerging industry-specific use cases
The maturity and accessibility of HPC have led to the emergence of new industry-specific use cases beyond traditional areas like genetics, government, military, and academia. Cloud-based HPC has extended its reach to various sectors such as finance, retail, life sciences, government, energy, media, automotive, aerospace, and more.
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In the financial services sector, HPC is used for fraud detection, risk analysis, and simulations. For example, Bankinter leverages HPC to simulate credit risk scenarios, while Mastercard uses machine learning algorithms on HPC systems to detect anomalies and identify fraud.
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Retailers are using HPC for consumer profiling, inventory analysis, logistics, and revenue predictions. Amazon relies heavily on supercomputers and predictive analysis to track purchasing behaviors.
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In life sciences, HPC is now utilized for molecular modeling and pharmaceutical design. Companies like Flinders University and ELEM Biotech use HPC for vaccine development and virtual clinical trials.
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Government, defense, and election campaigns use HPC for cybersecurity and simulations. For instance, defense contractor McCormick Stevenson runs simulation tests on missile and helicopter electronics.
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In the energy sector, HPC is applied to seismic data processing and wind energy enablement. Companies like Devon Energy use HPC cloud environments to speed up seismic applications, while Vestas utilizes InfiniBand-based clouds for weather simulations.
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Media companies rely on HPC for image analysis, computer-aided graphics, and rendering in film, media, and gaming. Disney and Mattel collaborate with Snowball Studios and use Oracle’s storage and networking software for image rendering.
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Automotive and discrete manufacturing industries use cloud-based HPC for complex simulations, such as crash test simulations, CFD analysis for cabin acoustics, and manufacturing production line simulations.
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The aerospace industry uses HPC for various scenarios, including CFD, structural analysis, and weather prediction. Advanced weather prediction is vital for airlines to reduce operational risks, and YellowDog assists a data and analytics company with weather forecasting from nanosatellite data.
Overall, HPC has found application in diverse industries due to its ability to handle massive computational workloads and offer real-time insights for complex problem-solving.
How I&O leaders can adopt HPC to drive innovation
Infrastructure and operations (I&O) professionals have the important task of evaluating and setting up high-performance computing options that will empower scientists, engineers, and researchers to find answers to critical questions that shape the organization’s future. While focusing on the technology is crucial, it’s equally important to consider the people who will use the HPC environment for scientific, engineering, and AI workloads.
Here are key steps to keep in mind when starting with HPC:
Start with research and relationship building: Conduct upfront research to build a solid business case for HPC. Form a team with individuals who understand the organization’s business needs and have expertise in the technology. This team is vital to your success as HPC tasks require experts in data science and technology.
Factor in IT considerations for on-premise deployments: HPC-specific infrastructure has unique needs, such as cooling and floor space. Higher-powered computing will require more cooling and may be costlier. It’s essential to plan for accommodating additional racks and banks in the data center.
Collaborate with security peers on regulations: Industries relying on HPC often face strict regulations. Plan for higher restrictions on operations and work closely with security and compliance peers to meet these requirements. Getting security experts involved early on prevents potential rework.
Source: Digital Realty
