What Are the Practical Uses of High-Performance Computing?

Industries such as manufacturing, life sciences, energy efficiency and extraction, financial services, government and defense, and scientific research face many of the same struggles. These challenges stem from their lack of ability to unpack vast amounts of data influx. High-performance computing solutions (HPC) are the answer to these problems. 

The market for HPC servers, storage, middleware, applications, and services was estimated at around $27 billion in 2018 and it is expected to grow to $39 billion by next year. HPC storage is expected to grow by over $2 billion from 2018 to 2023.

Clearly, HPC can help us optimize products and understand the world around us better. Applications such as innovative drug therapies, increased efficiency in energy, and improved fraud detection within the financial industry make high-performance computing essential for these industries. But what is it and how does it work?

What Is a High-Performance Computing (HPC) Cluster?

High-performance computing systems contain several components that work together efficiently. These subsystems include: 

• Compute– the computing portion of HPC runs the application. It ingests, analyzes, and computes the data. The setup for HPC is different than it has been for the past twenty years – where algorithms have parallelized features and the overall problem is broken into smaller, different parts, each running on a separate computer or core. These cores have to communicate partial answers to the others and it is stored on a device. With modern servers, each core might need to store recently computed information and the demands on the storage device increase as the core counts increase. With HPC, many of these servers use accelerators connected to the main CPU that accelerate portions of the application. These accelerators are known as GPGPUs and they can speed up applications by 50x while placing demands on the storage or networking infrastructure. 
• Storage– When a long-term simulation begins, large quantities of data keep the simulation running. Depending on the algorithm, more data might be required throughout the simulation. For example, if your team simulates the interaction between different drug molecules, thousands of molecular descriptions must be ingested. While the application runs, more of these descriptions might be investigated, which requires a low-latency and high-bandwidth storage infrastructure. HPC increases the efficiency of the data transfer to storage. 
• Networking– In the past, communications between servers and storage devices could limit the performance of the overall system. Each core performing the computing might need to communicate with thousands of other cores and request information from other nodes. But the network must be designed to handle the server-to-server communication, as well as multiple servers concurrently to the storage system. HPC improves this function. 
• Application Software- Software simulating physical processes runs across many cores and it is sophisticated. This sophistication is not only about the algorithms that construct the simulation, but also its reliance on libraries to manage networking, work distribution, and input and output to storage systems. HPC is designed to keep the system busy or else the investment for an HPC cluster won’t return at a high rate. 
• Orchestration- Supercomputers rarely have their entire system dedicated to one application. In an HPC cluster, you need software to let a scientist or engineer allocate a specific number of servers, GPUs, network bandwidth, and storage capabilities and capacities. These subsystems, along with the installation of the OS need to be handled with care. 

What Are the Practical Implications of HPC?

Manufacturing

Manufacturing companies have been relying on simulations for some time. Computer-aided engineering (CAE), which uses finite element analysis and mathematical techniques to simulate how physical objects will perform in real-world environments can store up to a TB of data per step. Since these applications run for days at a time, intermediate data must be checked and stored in a reliable, expedient fashion. 

Life Sciences 

Applications for life sciences can require more than a hundred computing cores. For example, with new drug designs, large databases describe how compounds interact with viruses and other molecules. For these simulations to work, the amount of data per compound can span into the TB range.

HPC can also help accomplish rapid genomic sequencing, which generates massive amounts of data that scientists need for further research. To store, manage, and share this data between teams, companies need storage solutions integrated with compute clusters and managed globally. 

Scientific Research 

The fastest supercomputers can dedicate many computing cycles and hundreds of thousands of cores to solving problems and investigating ongoing mysteries further. Questions about the universe, energy efficiency, and climate health can all be solved by the solutions that HPC solves. To do this, the system needs to accommodate massive amounts of data and store enormous quantities of both hot and cold data with long-running applications. 

Energy Alternatives 

HPC can be used to locate new energy deposits within the earth. This is done by sending seismic waves into the ground and collecting readings on the acoustic energy the application receives. HPC can analyze the large quantities of data collected. Because different materials below the earth’s surface reflect these waves, they enable geologists to determine the content below the surface. These applications can help determine both the amount of oil below the surface, as well as how much can be extracted safely and efficiently. 

Financial Services

Low-latency programmed trading has become common among many financial institutions so they can make better decisions using historical data. On the opposite side of the spectrum, high-frequency trading has never been more attainable because of HPC. The information gets fed into sophisticated algorithms that can determine definitively when to buy and when to sell. The budget for these systems to retrieve data comes down to microseconds, which means businesses need high-performance parallel file systems to retrieve the data they need. 

Data Protection

As industrial espionage continues to rise, the need to protect sensitive data also increases. As companies generate more and more data distributed throughout the organization, HPC represents the solution to prevent thieves from stealing sensitive data. 

Conclusion- What Are the Practical Use Cases of High-Performance Computing?

High-performance computing is one of the most important emerging technologies in the world due to its ability to provide new drug therapies, create solutions to climate change, and rapidly increase our understanding of how the universe works. It also carries the ability to protect data in an increasingly threatening environment as well as simplify financial transactions and investment decisions. Though it is complex, its benefits are irrefutable and companies will do well to try and understand how it will shape their industry in the future.