Topic: Computing (Page 43)

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πŸ”— Millipede Memory

πŸ”— Computing πŸ”— Computing/Computer hardware

Millipede memory is a form of non-volatile computer memory. It promised a data density of more than 1 terabit per square inch (1 gigabit per square millimeter), which is about the limit of the perpendicular recording hard drives. Millipede storage technology was pursued as a potential replacement for magnetic recording in hard drives and a means of reducing the physical size of the technology to that of flash media.

IBM demonstrated a prototype millipede storage device at CeBIT 2005, and was trying to make the technology commercially available by the end of 2007. However, because of concurrent advances in competing storage technologies, no commercial product has been made available since then.

πŸ”— Folding@Home

πŸ”— Computing πŸ”— Biology πŸ”— Computing/Software πŸ”— Stanford University πŸ”— Pharmacology πŸ”— Molecular Biology πŸ”— Molecular Biology/Molecular and Cell Biology πŸ”— Molecular Biology/Computational Biology

Folding@home (FAH or F@h) is a distributed computing project aimed to help scientists develop new therapeutics for a variety of diseases by the means of simulating protein dynamics. This includes the process of protein folding and the movements of proteins, and is reliant on simulations run on volunteers' personal computers. Folding@home is currently based at the University of Pennsylvania and led by Greg Bowman, a former student of Vijay Pande.

The project utilizes graphics processing units (GPUs), central processing units (CPUs), and ARM processors like those on the Raspberry Pi for distributed computing and scientific research. The project uses statistical simulation methodology that is a paradigm shift from traditional computing methods. As part of the client–server model network architecture, the volunteered machines each receive pieces of a simulation (work units), complete them, and return them to the project's database servers, where the units are compiled into an overall simulation. Volunteers can track their contributions on the Folding@home website, which makes volunteers' participation competitive and encourages long-term involvement.

Folding@home is one of the world's fastest computing systems. With heightened interest in the project as a result of the COVID-19 pandemic, the system achieved a speed of approximately 1.22 exaflops by late March 2020 and reached 2.43 exaflops by April 12, 2020, making it the world's first exaflop computing system. This level of performance from its large-scale computing network has allowed researchers to run computationally costly atomic-level simulations of protein folding thousands of times longer than formerly achieved. Since its launch on OctoberΒ 1, 2000, Folding@home was involved in the production of 226 scientific research papers. Results from the project's simulations agree well with experiments.

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πŸ”— Ostrich Algorithm

πŸ”— Computing

In computer science, the ostrich algorithm is a strategy of ignoring potential problems on the basis that they may be exceedingly rare. It is named for the ostrich effect which is defined as "to stick one's head in the sand and pretend there is no problem". It is used when it is more cost-effective to allow the problem to occur than to attempt its prevention.

πŸ”— List of device bandwidths

πŸ”— Computing πŸ”— Telecommunications πŸ”— Lists πŸ”— Computing/Networking

This is a list of interface bit rates, is a measure of information transfer rates, or digital bandwidth capacity, at which digital interfaces in a computer or network can communicate over various kinds of buses and channels. The distinction can be arbitrary between a computer bus, often closer in space, and larger telecommunications networks. Many device interfaces or protocols (e.g., SATA, USB, SAS, PCIe) are used both inside many-device boxes, such as a PC, and one-device-boxes, such as a hard drive enclosure. Accordingly, this page lists both the internal ribbon and external communications cable standards together in one sortable table.

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πŸ”— Reification (Computer Science)

πŸ”— Computing

Reification is the process by which an abstract idea about a computer program is turned into an explicit data model or other object created in a programming language. A computable/addressable objectβ€”a resourceβ€”is created in a system as a proxy for a non computable/addressable object. By means of reification, something that was previously implicit, unexpressed, and possibly inexpressible is explicitly formulated and made available to conceptual (logical or computational) manipulation. Informally, reification is often referred to as "making something a first-class citizen" within the scope of a particular system. Some aspect of a system can be reified at language design time, which is related to reflection in programming languages. It can be applied as a stepwise refinement at system design time. Reification is one of the most frequently used techniques of conceptual analysis and knowledge representation.

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πŸ”— Super-App

πŸ”— Computing πŸ”— Economics πŸ”— Apps

A super-app (also written as super app or superapp) is a mobile or web application that can provide multiple services including payment and financial transaction processing, effectively becoming an all-encompassing self-contained commerce and communication online platform that embraces many aspects of personal and commercial life. Notable examples of super-apps include Tencent's WeChat in China, and Grab in Southeast Asia.

πŸ”— Technical debt

πŸ”— Computing

Technical debt (also known as design debt or code debt, but can be also related to other technical endeavors) is a concept in software development that reflects the implied cost of additional rework caused by choosing an easy (limited) solution now instead of using a better approach that would take longer.

As with monetary debt, if technical debt is not repaid, it can accumulate 'interest', making it harder to implement changes. Unaddressed technical debt increases software entropy. Technical debt is not necessarily a bad thing, and sometimes (e.g., as a proof-of-concept) is required to move projects forward. On the other hand, some experts claim that the "technical debt" metaphor tends to minimize the impact, which results in insufficient prioritization of the necessary work to correct it.

As a change is started on a codebase, there is often the need to make other coordinated changes in other parts of the codebase or documentation. Changes required that are not completed are considered debt, and until paid, will incur interest on top of interest, making it cumbersome to build a project. Although the term is used in software development primarily, it can also be applied to other professions.

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πŸ”— Unum, a Better Number Format

πŸ”— Computing πŸ”— Computer science πŸ”— Computing/Software

Unums (universal numbers) are a family of number formats and arithmetic for implementing real numbers on a computer, proposed by John L. Gustafson in 2015. They are designed as an alternative to the ubiquitous IEEE 754 floating-point standard. The latest version is known as posits.

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πŸ”— Zope Object Database

πŸ”— Computing πŸ”— Computing/Software

The Zope Object Database (ZODB) is an object-oriented database for transparently and persistently storing Python objects. It is included as part of the Zope web application server, but can also be used independently of Zope.

Features of the ZODB include: transactions, history/undo, transparently pluggable storage, built-in caching, multiversion concurrency control (MVCC), and scalability across a network (using ZEO).

πŸ”— Flow-Matic

πŸ”— Computing

FLOW-MATIC, originally known as B-0 (Business Language version 0), was the first English-like data processing language. It was developed for the UNIVAC I at Remington Rand under Grace Hopper from 1955 to 1959, and helped shape the development of COBOL.

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