Explain Task Computing categories(High-Performance Computing, High-Throughput Computing, Many-Task Computing)

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 COMPUTING CATEGORIES

High-performance computing (HPC), high-throughput computing (HTC), and many-task computing (MTC) are some important computing categories.

High-Performance Computing

  • High-performance computing (HPC) refers to the technique of combining computing resources in order to tackle complex issues in research, engineering, or business. HPC is the use of distributed computing facilities to solve problems that need a high amount of processing power. Supercomputers and clusters have traditionally been built to enable HPC applications that are built to address challenging problems. Data drives revolutionary scientific discoveries, and game-changing technologies, and improves the quality of life for billions of people across the world. 
  • HPC lays the groundwork for scientific, industrial, and societal progress. The size and volume of data that companies work with are rising quickly as technologies such as the Internet of Things (IoT), artificial intelligence (AI), and 3-D imaging advance. The capacity to analyze data in real-time is critical for many purposes, including broadcasting a live sporting event, following a growing storm, testing new goods, evaluating market patterns, etc. Organizations must have lightning-fast, highly dependable IT infrastructure to process, store, and analyze vast volumes of data in order to stay ahead of the competition.
  • An HPC cluster is made up of hundreds or thousands of computing machines that are linked together through a network. Each server is referred to as a node. Each cluster's nodes operate in parallel with one another, increasing processing speed and delivering high-performance computing. The normal profile of HPC applications is made up of a significant number of compute-intensive activities that must be completed in a short period. Parallel and tightly connected processes are widespread, requiring the use of low-latency interconnection networks to reduce data interchange time. The metrics used to assess HPC floating-point operations per second (FLOPS), now tera-FLOPS, or even peta-FLOPS, identify the number of floating-point operations per second that a computing machine can execute. systems are

High-Throughput Computing

  • For many experimental scientists, scientific advancement and research quality are inseparably tied to computational throughput. In other words, most scientists are more interested in how many floating A point operations they can extract from their computing environment each month or year than in how many such operations the environment can offer them per second or minute. 
  • High-throughput computing (HTC) is the utilization of distributed computing resources for applications that require a huge amount of processing power over a lengthy period. HTC relies on the efficient control and utilization of all available computer resources.HTC systems must be strong and dependable for lengthy periods. Traditionally, heterogeneous computing grids (clusters, workstations, and volunteer PCs) have been utilized to support HTC HTC applications are made up of a large number of tasks whose execution may take weeks or months. 
  • Scientific simulations and statistical analysis are two examples of such applications. It is quite common to have independent tasks that can be scheduled in distributed resources because they do not need to communicate. HTC systems track success in terms of tasks performed every month. The primary problem that a typical HTC environment faces is maximizing the number of resources available to its: consumers. The main barrier that such an ecosystem must overcome in order to enlarge the pool of resources from which it may draw is distributed ownership of computer resources.

Many-Task Computing

  • Many-task computing (MTC) is a parallel computing technique in computational science that seeks to bridge the gap between two computing paradigms: high-throughput computing (HTC) and high-performance computing (HPC). The many-task computing (MTC) concept has lately gained popularity and applies to a wide range of applications.
  • MTC is similar to HTC, but it focuses on the usage of a large number of computing resources in a short amount of time to complete a large number of computational tasks. In a nutshell, MTC refers to high-performance calculations that include numerous independent activities that are linked together via file system operations. MTC is distinguished by the diversity of tasks, which may be radically different: small or big tasks, single-processor, or multiprocessor, compute-intensive or data-intensive, static, dynamic, homogeneous, or heterogeneous are all possibilities.
  • MTC applications have a general profile that includes loosely coupled applications that are generally communication-intensive but are not naturally expressed using the message-passing interface found in HPC, drawing attention to the many computations that are heterogeneous but not perfectly parallel. Given the enormous number of jobs that frequently comprise MTC applications, MTC may be supported by any distributed facility with a significant availability of computing elements. Supercomputers, massive clusters, and emerging cloud infrastructures are examples of such facilities.

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