What Is HPC (High Performance Computing)?

A single computer can’t handle some of the most complex and time-consuming tasks, like DNA sequencing or seismic analysis. It is possible to create an IT environment specifically designed for these computationally intensive workloads, paving the way for the level of data analysis we have never had before.

This article provides an introduction to high-performance computing and its potential impact on the way we conduct business. Continue reading to learn more about high-performance computing (HPC), how it works, and why it has the potential to push the boundaries of enterprise IT.

• Massive multi-dimensional datasets and massive amounts of data.
• Data analysis in real-time.
• Intensely powerful databases.
• The latest in AI and machine learning.

High-performance computing is of little use to the average user. Organizations that deal with large amounts of data and use CPU-intensive software are most likely to adopt HPC. Here are just a few of the many fascinating possibilities:

• Analysis of millions of patients’ disease progression to uncover insights and patterns of illness.
• Using a computer program to simulate a car crash instead of performing a real-world test.
• Identifying fraudulent transactions by analyzing millions of credit card records.
• Modeling how airflow affects an airplane’s wings.
• Identifying new materials for future use (e.g., for better batteries or more resilient buildings).

A few years ago, high-performance computing was mainly used by government agencies, research institutions, and the most powerful corporations. An HPC system on-site was only possible for these organizations.

When it comes to solving computationally-heavy problems in a timely and cost-effective manner, cloud computing has revolutionized HPC.

How does HPC Works?

Queue-based and transaction-by-transaction, a standard computer handles tasks. As many tasks as possible can be completed simultaneously on an HPC cluster.

Hundreds of nodes work parallel in an HPC architecture to increase processing speed. Hadoop MapReduce distributes computing tasks across all network nodes once an engineer configures and integrates nodes into the system.

A high-performance computing (HPC) system can be made up of three different types of hardware and systems:

Parallel Computing

As many as hundreds of processors can run calculations at the same time with parallel computing.

Cluster Computing

Using a cluster of computers, an administrator can create a shared resource that all of the computers in the system contribute. There must be a scheduler for such a system to function properly.

grid or distributed Computing

This connects the processing power of many computers in a network (either at a single or across multiple locations).

To deliver maximum performance, an HPC system’s various components (computers, networking, storage, and so on) must keep pace with one another. For example, data must move quickly between on-site servers and cloud storage for the networking component to keep up.

HPC systems can handle two distinct kinds of workloads:

• Incredibly parallel workloads can be broken down into small, easy-to-understand, and independent tasks. There is little to no communication between these tasks that run simultaneously.
• Complicated workloads that must communicate with each other during processing are referred to as “tightly coupled workloads.”

HPC can be run on physical hardware or in the cloud, depending on your needs (if you choose to set up a hybrid architecture). In either case, Linux is the most popular high-performance computing operating system.

Applications of HPC

• Use cases of financial technology (automatic and high-frequency trading, AI-based credit card fraud detection, real-time tracking of stock trends, complex risk analyses, self-guided tech support, etc.).
• Making predictions about storms and other unusual weather patterns.
• There are a variety of healthcare applications (vaccine research, testing drugs, and new cures, speeding up screening techniques, analyzing patient diagnoses, developing new therapies, studying disease patterns, etc.).
• Applied genomics examples (sequencing DNA, analyzing drug interactions, running protein analyses, genome mapping, etc.).
• Case studies in oil and gas (testing reservoir models, spatial analyses, locating new oil and gas resources, running a seismic or wind simulation, etc.).
• Simulators are used in pilot training and aircraft testing (e.g., airflow over the wings of planes or structural strength tests).
• Use cases for entertainment and media (rendering special effects, live event streaming, transcoding media files, processing an AR or VR video game, real-time image analysis, etc.).
• Improving customer service and product offerings by analyzing vast amounts of end-user data.
• Identifying new materials for batteries, buildings, semiconductors, and other applications.
• Working with cutting-edge blockchain technology
• Cases where the government is involved (climate modeling, nuclear stewardship, space exploration, etc.).
• Cases in retailing (inventory analysis, logistics, and supply chain optimization, sentiment analysis, etc.).
• Use cases in life sciences (molecular modeling, biology simulation, and protein docking).

Advantages

Processing Speed

The most important benefit of HPC is its ability to perform computations quickly. Compared to the weeks or even months, it would take a regular processor to complete the same task, an HPC system can process enormous amounts of data in a matter of seconds. A combination of HPC’s cluster/parallel computing, high-performance CPUs and graphics cards, low-latency networking, and block storage devices makes these speeds possible.

Less Physical Testing

The use of HPC to create simulations and reduce (or even eliminate) the need for physical tests is one benefit of HPC. In addition to saving time, some companies (such as car and airline manufacturers) also save money by eliminating the need to build and destroy prototypes.

Fault Tolerance

In the event of a node failure, the rest of the HPC system can continue to function normally. Although things will move more slowly, there will be no outages.

Business Opportunities

Expanding a company’s data-intensive workloads: HPC opens up new business opportunities.

Improvement of Operations

When it comes to everything from product design to pattern tracking, HPC opens up new possibilities that were previously unimaginable for any company, let alone a small business.
It is possible for an administrator to streamline current procedures by being able to crunch numbers and analyze data more quickly.

Lower Costs

HPC enables an app to run and produce results faster, resulting in lower costs. Consequently, you’ll be able to save both time and money over time. A pay-as-you-go model is another benefit of a cloud-based HPC system, which lowers IT costs by eliminating the need for capital expenditures.

Disadvantages

Large Investment

Be prepared to spend a lot of money if you decide to set up an HPC system on-site. The cost of procuring and maintaining a large number of computing nodes is considerable. An on-premises data center is expected, as are high upfront costs for hardware and a capable team of technicians.

Operating Costs

High cooling and power bills are part of the ongoing costs of running a supercomputer.

Aging HPC Equipment

On-premises infrastructure that is showing its age: The performance of an on-premise HPC system degrades over time. An HPC system must be constantly maintained because a large number of nodes increases the likelihood that one of them will fail. In addition, hardware will be out of date in a few years, resulting in additional expenses.

Lack of Portability

Code written for one HPC cluster may not work well on another, making portability an issue. It can take weeks or even months to move the entire HPC environment from point A to B, too.
On-site HPC clusters are difficult to manage and time-consuming to maintain. Low employee retention rates can be expected unless you’re willing to pay higher wages than other businesses can afford.

Long Buying Cycle

As HPC equipment is in high demand, you should consider long purchasing cycles. On-site research can be slowed down by waiting for hardware to arrive.

Future of HPC

HPC is increasingly being used by businesses across many sectors in their quest for faster big data analysis and next-generation simulations. According to industry experts, HPC market value is expected to rise to $44 billion by 2022 and $50 billion by 2023.

In the following years, the tech will have the most immediate impact on the following verticals and use cases:

• Precision medicine.
• Fraud detection in FinTech.
• Personalized interest rates.
• Business intelligence.
• Seismic analysis.
• Customized marketing.
• Chatbots.
• Internet of Things (IoT).
• Smart cities.
• Self-driving vehicles.
• Deep learning and neural networks.
• Data warehouses.

With more computing power and capacity to devote to their specific use cases, these companies will rely on HPC to speed up their research and innovation efforts.

Additionally, the HPC market is expected to benefit greatly from the emergence of cloud computing. HPC deployments in the cloud do away with the need for a company to invest millions of dollars in data center infrastructure and ongoing operating costs. Moving high-performance computing workloads to the cloud also has the following benefits:

• The time it takes to market is reduced.
• Adjustable resources allow users to adapt to changing IT requirements.
• Enables usage of cutting-edge technology (newest and fastest CPUs and GPUs, low-latency flash storage, RDMA networks, and top-tier levels of cloud security).

HPC will see a rise in the use of containers as well. Scalability, dependability, automation, and security are some benefits of using containers in HPC applications.