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Advanced computing

Advanced computing

Advanced computing entails sophisticated computing technology, including quantum, cloud, high-performance, and edge computing.

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OverviewApplicationsExamplesHigh-performance computing (HPC)Cloud computingEdge computingQuantum computingOther examplesTimelineTable: Companies in this industryTable: Further ResourcesReferences
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Industry
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Command and control (C2)
Command and control (C2)

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Information technology
Information technology
Computer Software
Computer Software
Edge computing
Edge computing
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Cloud computing
Cloud computing
Computer hardware
Computer hardware
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Computer
Overview

Advanced computing is a broad term used to describe specific types of high-end computing technology. Advanced computation research and innovation aim to improve computing technology in many aspects, including speed, reliability, efficiency, and security. It involves both new computing architectures and new software designs to develop next-generation computing systems.

Applications

Cutting-edge advanced computing techniques are utilized for enterprise and research, tackling some of the world's biggest challenges, including a wide variety of applications :

  • Cancer research
  • Identifying next-generation materials
  • Drug development
  • Weather forecasting
  • 3D rendering
  • AI and Machine learning
  • Financial services
Examples
High-performance computing (HPC)

HPC refers to systems with the ability to process data and perform calculations at high speeds, such as supercomputers. A supercomputer contains thousands of processors that work together to complete data-intensive and computation-heavy applications. While supercomputing refers to the process of complex and large calculations used by supercomputers, HPC is the use of multiple supercomputers to process complex and large calculations. However, both terms are often used interchangeably.

Supercomputers and other HPC scenarios can utilize parallel processing, using multiple CPUs to solve a single calculation at a given time.

HPC is made up of three main components:

  • Compute
  • Network
  • Storage

In HPC, compute servers are networked together in clusters. Algorithms are run simultaneously on these servers, with the cluster networked to the data storage to capture the output.

An HPC cluster can consist of hundreds or thousands of compute servers, or nodes, networked together. Nodes in each cluster work in parallel to boost processing speed and deliver high-performance computing.

Operating at maximum performance requires high speed and effective coordination of each component. For example, the storage component must be able to feed data to and from the compute servers at the same speed it is processed. HPC is limited by the slowest component present in the system.

Many scientific research firms, engineering companies, and other large enterprises with significant processing power requirements have moved from using on-location supercomputers to HPC services over the cloud.

Cloud computing

Cloud computing delivers on-demand computing services such as storage and processing power. Cloud computing is typically provided over the internet on a pay-as-you-go basis, allowing companies to outsource their computing requirements rather than owning and operating their own infrastructure or data center.

The primary benefit of cloud computing is avoiding the upfront costs and complexity of installing and maintaining IT infrastructure. Cloud service providers can benefit from the significant economies of scale when delivering the same service to a large customer base. Top cloud providers include the following:

  • Amazon Web Services (AWS)
  • Microsoft Azure
  • Google Cloud
  • Alibaba Cloud
  • IBM

There are three primary cloud computing services available:

  • Infrastructure as a Service (IaaS)—access to fundamental computing resources such as physical and virtual servers, networking, and storage
  • Platform as a Service (PaaS)—provides hardware, complete software stacks, infrastructure, and development tools to run, develop and manage applications
  • Software as a Service (SaaS)—also known as cloud-based software or cloud applications, the entire application is hosted in the cloud, run, and managed by the service provider
Edge computing

Edge computing is a form of computing for optimizing the performance of web applications and internet-connected devices by completing computational processes closer to the source of data. Edge computing reduces bandwidth consumption and latency by reducing the communication distance between clients and servers. Edge computing acts to decentralize the processes of cloud computing centers because it changes the geographic distribution of where computation is taking place.

Edge computing is often discussed in relation to IoT. Moving computing services closer to the source of data, such as an IoT device, offers a range of benefits, including rapidly analyzing real-time data, ideal for IoT sensors and devices.

Quantum computing

Quantum computation utilizes quantum mechanical effects such as superposition, entanglement, and interference to perform computation. Classical computation relies on the ability to store and manipulate binary integers (bits) generally made from silicon transistors. Instead, quantum computers make use of quantum bits (qubits) that can have the value 0, 1, or a superposition of these two states. Leveraging superposition and entanglement to create states that scale exponentially with the number of qubits offers the potential for dramatic improvements in computation power compared to classical computers.

Other examples

The field of advanced computing contains research into many new computing techniques, some of which share overlapping technology, goals, and processes.

The following are other examples of advanced computing technology:

  • Accelerated computing—the use of GPU acceleration to provide integrated solutions that offer advanced analytics, HPC, and AI
  • Cognitive computing—uses computerized models to simulate the human thought process in complex situations where the answers may be ambiguous and uncertain
  • Perceptual computing—computers that are able to better sense or analyze the environment around them and respond accordingly
  • Neural computing (Neural network)—a series of algorithms that recognize underlying relationships in a set of data through a process that mimics how the human brain operates
  • Evolutionary Computation—stochastic algorithms whose search methods model some natural phenomena
  • Granular computing—an emerging paradigm in computing and applied mathematics where data or information is divided into so-called granules. A collection of entities that in the scope of granular computing, usually originate from numerical analysis to group entities together at a certain level of granularity, thanks to their similarity, functional or physical adjacency, or indistinguishability

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Companies in this industry

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