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High-Performance Computing (HPC): Enhancing Computational Efficiency
High-Performance Computing (HPC) involves utilizing parallel data processing to improve computational performance and handle complex calculations. HPC achieves these goals by aggregating computational power, enabling even advanced applications to run efficiently, reliably, and quickly according to user demands and expectations. Thus, it offers significantly greater power and performance compared to traditional computers, workstations, and servers.
In today’s modern world, groundbreaking discoveries and innovations are only possible with advanced technology, data, and computing. As sophisticated technologies like Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) evolve, they demand massive amounts of data. They also require HPC, as HPC systems can perform up to four billion computations per second, compared to standard laptops or desktops, which can manage a maximum of three billion computations per second (with a 3 GHz processor).
HPC helps overcome numerous computational barriers that regular computers and processors usually face. The benefits of HPC are extensive and include the following:
HPC is primarily about lightning-fast processing, enabling HPC systems to perform vast computations rapidly. In comparison, traditional processors and computing systems take significantly longer—days, weeks, or even months—to complete these calculations.
HPC systems typically utilize the latest processors, GPUs, low-latency network fabrics, and block storage devices to enhance processing speed and computational performance.
Since an HPC system can process faster, applications can execute and respond quicker, saving time and costs. Additionally, many of these systems are available in “pay-as-you-go” modes and can scale up or down as needed, further enhancing affordability.
Many modern applications require extensive physical testing before being released for public or commercial use. Autonomous vehicles are one example. Researchers, developers, and testers can create powerful simulations using HPC systems, minimizing or even eliminating the need for costly or repetitive physical testing.
It’s crucial that these different components operate at similar speeds or performance levels. If they fail to synchronize, HPC cannot occur, and the entire system may fail. For example, servers must effectively receive and process data from storage components, while these components need to quickly feed data to the servers to support HPC. Similarly, network components must support seamless high-speed data transfer between other components.
HPC systems can handle various workloads, primarily categorized into parallel and tightly coupled workloads:
In these workloads, computational problems are divided into smaller, independent tasks that can run simultaneously at high speed. These workloads often do not interact with each other. Examples include risk simulations, logistics simulations, text searches, and molecular modeling.
When workloads are divided into smaller tasks and continuously interact during their processing, they are said to be tightly coupled. This typically occurs with workloads across different nodes in a cluster. Common examples include car crash simulations, spatial simulations, weather forecasting models, and traffic management.
Both types of workloads require high processing speed and accurate output, which necessitates HPC.
HPC is utilized in many real-world scenarios to solve complex problems in science, business, and engineering. Many academic institutions also use HPC systems. Certain government organizations, especially in the military, rely on HPC for sophisticated applications. As demand for processing power and speed for real-world applications increases, HPC is likely to attract businesses of all sizes, particularly for transaction processing and data warehousing.
A supercomputer is one of the most well-known examples of HPC, comprising many computers and processors working together to achieve parallel processing and high performance.
While HPC has significantly advanced in recent decades, several obstacles still hinder its widespread adoption:
Many of these challenges arise from deploying on-premises HPC systems. Cloud-based technologies specifically designed for HPC workloads—offering vast capacity and a “pay-as-you-go” model—can provide a feasible solution to these challenges.
Explore the Comprehensive HPC Guide in Data Centers to learn how HPC services bring computational power to more organizations, maximize HPC application performance, implement GPUs for HPC, and discover High-Performance Computing as a Service.