HPC is technology that uses clusters of powerful processors, working in parallel, to process massive multi-dimensional datasets (big data) and solve complex problems at extremely high speeds. HPC systems typically perform at speeds more than one million times faster than the fastest commodity desktop, laptop or server systems.
For decades the HPC system paradigm was the supercomputer, a purpose-built computer that embodies millions of processors or processor cores. Supercomputers are still with us; at this writing, the fastest supercomputer is the US-based Frontier (link resides outside ibm.com), with a processing speed of 1.102 exaflops, or quintillion floating point operations per second (flops). But today, more and more organizations are running HPC solutions on clusters of high-speed computers servers, hosted on premises or in the cloud.
HPC workloads uncover important new insights that advance human knowledge and create significant competitive advantage. For example, HPC is used to sequence DNA, automate stock trading, and run artificial intelligence (AI) algorithms and simulations—like those enabling self-driving automobiles—that analyze terabytes of data streaming from IoT sensors, radar and GPS systems in real time to make split-second decisions.
A standard computing system solves problems primarily using serial computing—it divides the workload into a sequence of tasks, and then executes the tasks one after the other on the same processor.
In contrast, HPC leverages
As recently as a decade ago, the high cost of HPC—which involved owning or leasing a supercomputer or building and hosting an HPC cluster in an on-premises data center—put HPC out of reach for most organizations.
Today HPC in the cloud—sometimes called HPC as a service, or HPCaaS—offers a significantly faster, more scalable and more affordable way for companies to take advantage of HPC. HPCaaS typically includes access to HPC clusters and infrastructure hosted in a cloud service provider’s data center, plus ecosystem capabilities (such as AI and data analytics) and HPC expertise.
Today HPC in the cloud is driven by three converging trends:
HPC applications have become synonymous with AI apps in general, and with machine learning and deep learning apps in particular; today most HPC systems are created with these workloads in mind. These HPC applications are driving continuous innovation in:
Healthcare, genomics and life sciences. The first attempt to sequence a human genome took 13 years; today, HPC systems can do the job in less than a day. Other HPC applications in healthcare and life sciences include drug discovery and design, rapid cancer diagnosis, and molecular modeling.
Financial services. In addition to automated trading and fraud detection (noted above), HPC powers applications in Monte Carlo simulation and other risk analysis methods.
Government and defense. Two growing HPC use cases in this area are weather forcasting and climate modeling, both of which involve processing vast amounts of historical meteorological data and millions of daily changes in climate-related data points. Other government and defense applications include energy research and intelligence work.
Energy. In some cases overlapping with government and defense, energy-related HPC applications include seismic data processing, reservoir simulation and modeling, geospatial analytics, wind simulation and terrain mapping.
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