Understanding High-Performance Computing (HPC) and Its Applications

HPC plays a crucial role in advancing scientific and technological innovation, driving economic growth, and addressing some of the world's most pressing challenges.

FREMONT, CA: 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. 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.

How Does HPC Work?

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High-performance computing (HPC) or supercomputing environments are used to handle extremely large and complex tasks that cannot be processed by a single computer, such as DNA sequencing. In HPC, multiple nodes or computers work together in a cluster to perform massive amounts of computing within a short time. Cloud automation is used to create and remove these clusters to reduce costs. Embarrassingly parallel and tightly coupled workloads are the two most common types of workloads that can be run on HPC.

Tightly Coupled Workloads

The usual approach for handling a large workload that is shared among multiple nodes is to divide it into smaller tasks and establish continuous communication among them. This allows the nodes to exchange information as they conduct their respective processing. This approach is commonly applied in various fields such as computational fluid dynamics, weather forecasting, material simulations, automobile crash simulations, geospatial simulations, and traffic management.

Why is HPC Important?

For many years, high-performance computing (HPC) has been a crucial element in academic research and industrial innovation. It aids engineers, data scientists, designers, and other researchers in tackling intricate and extensive problems in significantly less time and expense than traditional computing methods.

Reduced Physical Testing: High-performance computing (HPC) can be utilised to create simulations that can replace the requirement for conducting physical tests. For instance, in the case of testing automotive accidents, it is more convenient and cost-effective to generate a simulation rather than to carry out a crash test.

Speed: Thanks to modern CPUs, GPUs, and high-speed networking technologies like RDMA, along with the use of all-flash storage devices for local and block data storage, high-performance computing (HPC) can now complete complex calculations in mere minutes, which used to take weeks or even months to complete.

Cost: By providing quicker responses, HPC can save organisations both time and money. Furthermore, with cloud-based HPC solutions, even small companies and startups can take advantage of HPC workloads at a reasonable cost by paying only for what they use and scaling their resources as required.

Innovation: High-performance computing (HPC) is a key driver of innovation across a broad range of industries and has been instrumental in achieving significant scientific breakthroughs that have enhanced people's quality of life globally.

HPC Use Case—Which Industries Use High-Performance Computing?

HPC is being used by many Fortune 1000 companies in various industries, and its usage is increasing. The global HPC market is expected to hit USD 44 billion by 2022, according to Hyperion Research.

The following is a list of industries that use HPC and the types of tasks they use HPC to accomplish:

Aerospace: This refers to the development of intricate computer models, such as those that simulate the flow of air over the wings of aircraft.

Manufacturing: Running simulations, including those for autonomous driving, to aid in the creation, production, and testing of new products, leading to lighter components, safer vehicles, more efficient processes, and innovative solutions.

Financial Technology (fintech): Conducting intricate risk assessments, engaging in high-frequency trading, developing financial models, and detecting instances of fraud.

Genomics: This refers to tasks like reading genetic codes, examining how medicines interact with the body, and studying proteins to assist with research on family lineage.

Healthcare: This refers to using HPC to conduct research on medication, produce vaccines, and develop new treatment options for both common and uncommon medical conditions.

Media and Entertainment: This involves generating animated visuals, producing special effects for films, converting large media files, and developing captivating entertainment experiences.

Oil and Gas: Conducting spatial analyses and examining reservoir models to make predictions about the location of oil and gas resources, as well as running simulations like fluid flow and seismic processing.

Where is HPC Performed?

HPC can be carried out using three different models: on-premise, in the cloud, or in a hybrid deployment that combines both.

An on-premise HPC deployment involves an organisation building and managing its own HPC cluster, which includes servers, storage, and other infrastructure. However, in a cloud HPC deployment, a third-party provider manages the infrastructure and organisations only pay for the resources they use.

Certain companies choose to use a hybrid deployment strategy, particularly those that have already invested in on-premise infrastructure but also wish to leverage the cloud's speed, flexibility, and cost-effectiveness. Such companies can run some of their HPC workloads continuously in the cloud while using cloud services on an as-needed basis, particularly when on-premise queue time becomes problematic.

HPC Cloud—What are the Key Considerations When Choosing a Cloud Environment?

Cloud providers vary in their capabilities, and not all of them are suitable for HPC workloads, which require high performance and reliability. When choosing a cloud provider, there are four key factors to consider.

Leading-Edge Performance: It is important to ensure that cloud provider has access to and consistently updates their technology with the latest processors, storage, and network advancements. The provider should offer a large capacity and top-tier performance that matches or surpasses what is typically found in on-premise deployments.

Experience With HPC: When choosing a cloud provider for HPC workloads, it is important to select a provider with extensive experience running such workloads for various clients. The provider's cloud service should be designed to provide optimal performance, even during peak periods, such as when running multiple simulations or models. In some cases, bare metal computer instances may offer more reliable and powerful performance.

What is the Future of HPC?

The High-Performance Computing (HPC) market is experiencing growth across various industries, with the global market projected to increase from USD 31 billion in 2017 to USD 50 billion in 2023. This growth is expected to continue, with cloud-based HPC deployments playing a significant role due to their increasing reliability and performance, which eliminates the need for companies to invest heavily in data centre infrastructure and related costs. In the near future, big data and HPC are likely to converge, with large clusters of computers being used for both tasks, resulting in greater computing power and capacity for each. This convergence is expected to lead to further breakthroughs in research and innovation.

Flexibility to Lift and Shift: High-Performance Computing (HPC) workloads must operate the same in the cloud as they do on-premise. When moving workloads to the cloud using a lift-and-shift approach, the simulations must produce consistent results with previous ones, regardless of whether they were run a week ago or a decade ago. This is particularly important in industries where data and computations from previous years are used for year-to-year comparisons. In fields such as aerodynamics, automobiles, and chemistry, the computations remain the same, and the results must not change.

No Hidden Costs: Cloud services generally operate under a pay-as-you-go system, so it's essential to have a clear understanding of the expenses associated with each use of the service. Some users find themselves taken aback by the costs associated with outbound data movement or egress, which can be overlooked despite having to pay per transaction and data access requests. Therefore, it's crucial to be aware of egress costs.

High-Performance Computing (HPC) refers to the use of advanced computing techniques and technologies to solve complex computational problems that are beyond the capabilities of conventional computing systems. HPC systems typically consist of large-scale clusters of interconnected computers or servers that work together to process massive amounts of data and perform complex simulations and modelling tasks.

HPC is used in a wide range of fields, including scientific research, engineering, finance, and medicine, to tackle problems such as weather forecasting, protein folding, drug discovery, and financial modelling. HPC systems are characterised by their high processing power, large memory capacity, high-speed interconnects, and advanced software tools for parallel processing and data management.