Table of Contents
How Does HPC Work?There are three key components of high-performance computing solutions: compute, network, and storage. In order to develop a high performance computing architecture, multiple computer servers are networked together to form a cluster. Algorithms and software programs are executed concurrently on the servers in the cluster. To get the results, the cluster is networked to data storage. These modules function together to complete different tasks. To achieve maximum efficiency, each module must keep pace with others, else the performance of the entire HPC infrastructure would deteriorate.
Accessing Software on HPC SystemsAs HPC systems are being used by many users with different requirements, they usually have multiple versions of frequently used software packages installed. As it is not easy to install and use many versions of a package at the same time, this system uses environment modules that allow users to configure the software environment with the specific version required.
Why Is High-Performance Computing Important?Usually, some problems cannot be resolved on a commodity computer within a limited time frame. Sometimes, there are issues with the execution because of the limited availability of resources. In such cases, high-performance computing is the best solution to overcome these restrictions with the use of specialized hardware or by collecting computational power from different units. The consequent allocation of operations and data across different units needs the concept of parallelization. According to a report by MarketsandMarkets, by the year 2022, the HPC market is expected to grow from USD 32.11 Billion in 2017 to USD 44.98 Billion. With an increasing demand for efficient computing, reliable storage system, and enhanced scalability, the adoption of HPC systems is set to increase in the coming years among end-users. While the use of high-performance computing matters for a number of reasons, there are at least five reasons which are conceptually distinct.
- Every step-change in HPC signifies an order of magnitude change, which opens up the potential for new applications or improved use of the current ones.
- With the introduction of computational simulation, HPC is changing the scientific method itself.
- HPC would be required as a platform of innovation to manage the huge amount of data.
- Reduced costs, along with growing capabilities, are modifying HPC systems and making them available to a range of institutional and commercial users, including SMBs.
- HPC characterizes an opportunity to tackle the erosion of Moore’s Law(at least for high-performance processes).
High-Performance Computing Use CasesPreviously used by software developers and theoretical scientists, high-performance computing is now becoming more important as a research tool in different areas. Below are some of the examples:
- Financial services: HPC is being used to monitor real-time stock trends and automate trading.
- Research labs: HPC is used by scientists to find sources of renewable energy, create new materials, make predictions about storms, and study the evolution of the universe. HPC is also being used by researchers in geology, social media, brain imaging, semantics, economics, genomics, and even music.
- Healthcare: HPC is being used by healthcare specialists to cure diseases such as diabetes and cancer for more accurate and faster diagnosis of the patient.
- Entertainment industry: Professionals in the media and entertainment industry use HPC to edit feature films, stream live events, and render special effects.
- Oil and gas: With the help of high-performance computing systems, one can identify where to drill for new wells. It helps businesses increase production from existing wells.
- Machine Learning and Artificial Intelligence: HPC can be used to improve cancer screening methods, uncover credit card fraud, offer self-assisted technical support, and teach self-driving vehicles.
- Industry: HPC can be used to improve products, reduce the time taken to develop new products, and also reduce production costs.
- Big Data: As our ability to gather information increases, high-performance computing systems can be highly useful to analyze this data.