With solutions tuned explicitly for high-performance computing (HPC), researchers and engineers can make transformational discoveries and build innovative processes, systems, and products. Within a single system or across multiple systems, on-premises, or augmented with the cloud, HPC is more accessible than ever before.
What is High-Performance Computing (HPC)?
High-Performance Computing (HPC) refers to the practice of aggregating computing power in a way that delivers much higher horsepower than traditional computers and servers. HPC, or supercomputing, is like everyday computing, only more powerful. It is a way of processing huge volumes of data at very high speeds using multiple computers and storage devices as a cohesive fabric. HPC makes it possible to explore and find answers to some of the world’s biggest problems in science, engineering, and business.
Today, HPC is used to solve complex, performance-intensive problems – and organizations are increasingly moving HPC workloads to the cloud. HPC in the cloud is changing the economics of product development and research because it requires fewer prototypes, accelerates testing, and decreases time to market.
Why is HPC important?
It is through data that groundbreaking scientific discoveries are made, game-changing innovations are fueled, and quality of life is improved for billions of people around the globe. High-Performance Computing is the foundation for scientific, industrial, and societal advancements.
As technologies like the Internet of Things (IoT), artificial intelligence (AI), and 3-D imaging evolve, the size and amount of data that organizations have to work with are growing exponentially. For many purposes, such as streaming a live sporting event, tracking a developing storm, testing new products, or analyzing stock trends, the ability to process data in real-time is crucial.
To keep a step ahead of the competition, organizations need lightning-fast, highly reliable IT infrastructure to process, store, and analyze massive amounts of data.
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, for 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.
Benefits of High-Performance Computing
HPC helps overcome numerous computational barriers that conventional PCs and processors typically face. The benefits of HPC are many and include the following.
- High speeds: HPC is mainly about lightning-fast processing, which means HPC systems can perform massive amounts of calculations very quickly. In comparison, regular processors and computing systems would take longer – days, weeks, or even months – to perform these same calculations. HPC systems typically use the latest CPUs and GPUs, as well as low-latency networking fabrics and block storage devices, to improve processing speeds and computing performance.
- Lower cost: Because an HPC system can process faster, applications can run faster and yield answers quickly, saving time or money. Moreover, many such systems are available in “pay as you go” modes and can scale up or down as needed, further improving their cost-effectiveness.
- Reduced need for physical testing: Many modern-day applications require a lot of physical testing before they can be released for public or commercial use. Self-driven vehicles are one example. Application researchers, developers, and testers can create powerful simulations using HPC systems, thus minimizing or even eliminating the need for expensive or repeated physical tests.
HPC system designs
What gives High-Performance Computing 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 a scheduler, computes, and storage capabilities.
- Distributed and grid 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 the network, computing data, and instrument resources.
HPC use cases
Deployed on-premises, at the edge, or in the cloud, High-Performance Computing solutions are used for a variety of purposes across multiple industries. Examples include:
- Research labs. HPC is used to help scientists find sources of renewable energy, understand the evolution of our universe, predict and track storms, and create new materials.
- Media and entertainment. HPC is used to edit feature films, render mind-blowing special effects, and stream live events around the world.
- Oil and gas. HPC is used to more accurately identify where to drill for new wells and to help boost production from existing wells.
- Artificial intelligence and machine learning. HPC is used to detect credit card fraud, provide self-guided technical support, teach self-driving vehicles, and improve cancer screening techniques.
- Financial services. HPC is used to track real-time stock trends and automate trading.
- HPC is used to design new products, simulate test scenarios, and make sure that parts are kept in stock so that production lines aren’t held up.
- HPC is used to help develop cures for diseases like diabetes and cancer and to enable faster, more accurate patient diagnosis.
What is the future of HPC?
Businesses and institutions across multiple industries are turning to HPC, driving growth that is expected to continue for many years to come. The global HPC market is expected to expand from US$31 billion in 2017 to US$50 billion in 2023. As cloud performance continues to improve and become even more reliable and powerful, much of that growth is expected to be in cloud-based HPC deployments that relieve businesses of the need to invest millions in data center infrastructure and related costs.
In the near future, expect to see big data and HPC converging, with the same large cluster of computers used to analyze big data and run simulations and other HPC workloads. As those two trends converge, the result will be more computing power and capacity for each, leading to even more groundbreaking research and innovation.