High performance Computing

It is the use of parallel processing for running advanced application programs efficiently, relatives, and quickly. The term applies especially is a system that function above a teraflop (10¹²) (floating opm per second). The term High-performance computing is occasionally used as a synonym for supercomputing. Although technically a supercomputer is a system that performs at or near currently highest operational rate for computers. Some supercomputers work at more than a petaflop (10¹²) floating points opm per second. The most common HPC system all scientific engineers & academic institutions. Some Government agencies particularly military are also relying on APC for complex applications. 

High-performance Computers: 

High Performance Computing (HPC) generally refers to the practice of combining computing power to deliver far greater performance than a typical desktop or workstation, in order to solve complex problems in science, engineering, and business.

Processors, memory, disks, and OS are elements of high-performance computers of interest to small & medium size businesses today are really clusters of computers. Each individual computer in a commonly configured small cluster has between one and four processors and today ‘s processors typically are from 2 to 4 crores, HPC people often referred to individual computers in a cluster as nodes. A cluster of interest to a small business could have as few as 4 nodes on 16 crores. Common cluster size in many businesses is between 16 & 64 crores or from 64 to 256 crores. The main reason to use this is that in its individual node can work together to solve a problem larger than any one computer can easily solve. These nodes are so connected that they can communicate with each other in order to produce some meaningful work. There are two popular HPC’s software i. e, Linux, and windows. Most of installations are in Linux because of Linux legacy in supercomputer and large scale machines. But one can use it with his / her requirements. 

Importance of High performance Computing :

1. It is used for scientific discoveries, game-changing innovations, and to improve quality of life.
2. It is a foundation for scientific & industrial advancements.
3. It is used in technologies like IoT, AI, 3D imaging evolves & amount of data that is used by organization is increasing exponentially to increase ability of a computer, we use High-performance computer.
4. HPC is used to solve complex modeling problems in a spectrum of disciplines. It includes AI, Nuclear Physics, Climate Modelling, etc.
5. HPC is applied to business uses, data warehouses & transaction processing.

Need of High performance Computing :

1. It will complete a time-consuming operation in less time.
2. It will complete an operation under a light deadline and perform a high numbers of operations per second.
3. It is fast computing, we can compute in parallel over lot of computation elements CPU, GPU, etc. It set up very fast network to connect between elements.

Need of ever increasing Performance :

1. Climate modeling
2. Drug discovery
3. Data Analysis
4. Protein folding
5. Energy research

How Does HPC Work?

User/Scheduler → Compute cluster → Data storage 

To create a high-performance computing architecture, multiple computer servers are networked together to form a compute cluster. Algorithms and software programs are executed simultaneously on the servers, and the cluster is networked to data storage to retrieve the results. All of these components work together to complete a diverse set of tasks.

To achieve maximum efficiency, each module must keep pace with others, otherwise, the performance of the entire HPC infrastructure would suffer. 

Challenges with HPC 

1. Cost: The cost of the hardware, software, and energy consumption is enormous, making HPC systems exceedingly expensive to create and operate. Additionally, the setup and management of HPC systems require qualified workers, which raises the overall cost.
2. Scalability: HPC systems must be made scalable so they may be modified or expanded as necessary to meet shifting demands. But creating a scalable system is a difficult endeavour that necessitates thorough planning and optimization. 
3. Data Management: Data management can be difficult when using HPC systems since they produce and process enormous volumes of data. These data must be stored and accessed using sophisticated networking and storage infrastructure, as well as tools for data analysis and visualization. 
4. Programming: Parallel programming techniques, which can be more difficult than conventional programming approaches, are frequently used in HPC systems. It might be challenging for developers to learn how to create and optimise algorithms for parallel processing.
5. Support for software and tools: To function effectively, HPC systems need specific software and tools. The options available to users may be constrained by the fact that not all software and tools are created to function with HPC equipment.
6. Power consumption and cooling: To maintain the hardware functioning at its best, specialised cooling technologies are needed for HPC systems’ high heat production. Furthermore, HPC systems consume a lot of electricity, which can be expensive and difficult to maintain.

Applications of HPC 

High Performance Computing (HPC) is a term used to describe the use of supercomputers and parallel processing strategies to carry out difficult calculations and data analysis activities. From scientific research to engineering and industrial design, HPC is employed in a wide range of disciplines and applications. Here are a few of the most significant HPC use cases and applications:

1. Scientific research: HPC is widely utilized in this sector, especially in areas like physics, chemistry, and astronomy. With standard computer techniques, it would be hard to model complex physical events, examine massive data sets, or carry out sophisticated calculations. 
2. Weather forecasting: The task of forecasting the weather is difficult and data-intensive, requiring sophisticated algorithms and a lot of computational power. Simulated weather models are executed on HPC computers to predict weather patterns. 
3. Healthcare: HPC is being used more and more in the medical field for activities like medication discovery, genome sequencing, and image analysis. Large volumes of medical data can be processed by HPC systems rapidly and accurately, improving patient diagnosis and care.
4. Energy and environmental studies: HPC is employed to simulate and model complex systems, such as climate change and renewable energy sources, in the energy and environmental sciences. Researchers can use HPC systems to streamline energy systems, cut carbon emissions, and increase the resilience of our energy infrastructure.
5. Engineering and Design: HPC is used in engineering and design to model and evaluate complex systems, like those found in vehicles, buildings, and aeroplanes. Virtual simulations performed by HPC systems can assist engineers in identifying potential problems and improving designs before they are built.