What is high-performance computing (HPC)?

High-performance computing (HPC) is a technology that harnesses the power of supercomputers or computer clusters to solve complex problems requiring massive computation.

Close up of Circuits

Why high-performance computing is important

HPC lets users process large amounts of data quicker than a standard computer, leading to faster insights and giving organizations the ability to stay ahead of the competition. HPC solutions can be one million times more powerful than the fastest laptop. This power allows enterprises to run large analytical computations, such as millions of scenarios that use up to terabytes (TBs) of data. For example, scenario planning requires large analytical computations an HPC provides, such as weather forecasting or risk management assessments. Organizations can also run design simulations before physically building items like chips or cars. In sum, HPC empowers superior performance, allowing companies to do more while spending less.

Another major application for HPC is in the fields of medical and material advancements. For instance, HPC can be deployed to:

Combat cancer: Machine learning algorithms will help supply medical researchers with a comprehensive view of the U.S. cancer population at a granular level of detail.

Identify next-generation materials: Deep learning could help scientists identify materials for better batteries, more resilient building materials and more efficient semiconductors.

Understand patterns of disease: Using a mix of artificial intelligence (AI) techniques, researchers will identify patterns in the function, cooperation, and evolution of human proteins and cellular systems.


How does high-performance computing work?

Standard computers perform tasks on a transaction-by-transaction basis, which means the next transaction, or job, happens only when the computer completes the previous one. In contrast, HPC uses all available resources or processors to complete many jobs at once. Therefore, the time it takes to complete a job depends on the resources available and the design used. And if there are more jobs than there are processors, then the HPC system forms a queue.

For the most part, HPC occurs on supercomputers. These powerful systems help organizations solve problems that could otherwise be insurmountable. And these problems, or tasks, require processors that can carry out instructions faster than standard computers, sometimes running many processors in parallel to obtain answers within a practical duration.

In addition to parallel processing, HPC jobs also require fast disks and high-speed memory. Therefore, HPC systems include computing and data-intensive servers with powerful CPUs that can be vertically scaled and available to a user group. HPC systems can also have many powerful graphics processing units (GPUs) for graphics-intensive tasks, too. Notably, however, each server only hosts a single application.

HPC systems can also scale horizontally by way of clusters. These clusters consist of networked computers, including scheduler, compute, and storage capabilities. Single HPC clusters are as large as 100 thousand or more compute cores, as an example. Unlike single server systems, clusters can accommodate multiple applications and resources for a user group. And while managed by policy-based scheduling, a cluster's combined compute power and commodity resources can handle a dynamic workload.


HPC system designs

What gives HPC solutions a power and speed advantage over standard computers is their hardware and system designs. There are three HPC designs used: parallel computing, cluster computing, and grid and distributed computing.

Parallel computing

Parallel computing HPC systems involve hundreds of processors, with each processor running calculation payloads simultaneously.

Cluster computing

Cluster computing is a type of parallel HPC system consisting of a collection of computers working together as an integrated resource. It includes scheduler, compute, and storage capabilities.

Grid and distributed computing

Grid and distributed computing HPC systems connect the processing power of multiple computers within a network. The network can be a grid at a single location or distributed across a wide area in different places, linking network, compute, data and instrument resources.


HPC and the cloud

With advancements in cloud technologies, HPC solutions have become more accessible and affordable to enterprises. Today, organizations can access a wider variety of HPC applications and dynamic resources with only a high-speed internet connection with cloud benefits, such as flexibility, efficiency and strategic value.


HPC cloud benefits

Flexibility

Users can scale services to fit their needs, customize applications and access specialized HPC data centers from anywhere with an internet connection.

Efficiency

Users can process more HPC workloads and gain labor cost savings without worrying about underlying infrastructure costs or maintenance.

Strategic value

HPC cloud services give enterprises a competitive advantage by providing the most innovative technology available that meets capacity needs.


How is high-performance computing used?

Today, HPC has become synonymous with AI. For example, Summit and Sierra supercomputers were built with AI workloads in mind. But they're also helping model supernovas, pioneer new materials, and explore cancer, genetics and the environment. 

HPC is also indispensable when it comes to:

  • Big data: massive multi-dimensional datasets
  • Data analytics
  • Extreme performance database
  • Machine learning

Where is high-performance computing used?

Automotive and aerospace

  • CFD-aerodynamic modeling
  • FEA-impact and structural strength analysis
  • CAD and CAM

Banking, financial services markets and insurance

  • Monte Carlo simulations
  • Risk analysis
  • Fraud detection

Electronics design automation (EDA)

  • Chip design and optimization
  • Circuit simulation and verification
  • Manufacturing optimization

Film, media and gaming

  • Rendering
  • Computer-aided graphics
  • Computer-generated images (CGI)
  • Transcoding and encoding
  • Real-time image analysis and processing

Government and defense

  • Intelligence agency
  • Fraud analysis
  • Climate modeling
  • Weather forecasting
  • Energy
  • Nuclear stewardship
  • Exploration

Life sciences

  • Genomic processing and sequencing
  • Pharmaceutical design
  • Molecular modeling and biology simulation
  • Protein docking

Oil and gas

  • Seismic data processing
  • Reservoir simulation and modeling
  • Geospatial analytics
  • Terrain and topology mapping
  • CFD-aerodynamic modeling
  • Wind simulation

Retail

  • Inventory analysis
  • Logistics and supply chain optimization
  • Sentiment analysis
  • Marketing offers

 

 


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