What do you mean by the word COMPUTER?

Question

I like to know the meaning of Computer & its characteristics. It will be appreciated if I know the funtionalities of a computer briefly...

Thnaks

Answer 1

Device that makes computations.

Answer 2

Quick definitions (computer)

noun: a machine for performing calculations automatically
noun: an expert at calculation (or at operating calculating machines)

A programmable machine. The two principal characteristics of a computer are:

*It responds to a specific set of instructions in a well-defined manner.
*It can execute a prerecorded list of instructions (a program).
Modern computers are electronic and digital. The actual machinery -- wires, transistors, and circuits -- is called hardware; the instructions and data are called software.

All general-purpose computers require the following hardware components:

*memory : Enables a computer to store, at least temporarily, data and programs.
*mass storage device : Allows a computer to permanently retain large amounts of data. Common mass storage devices include disk drives and tape drives.
*input device : Usually a keyboard and mouse, the input device is the conduit through which data and instructions enter a computer.
*output device : A display screen, printer, or other device that lets you see what the computer has accomplished.
*central processing unit (CPU): The heart of the computer, this is the component that actually executes instructions.

In addition to these components, many others make it possible for the basic components to work together efficiently. For example, every computer requires a bus that transmits data from one part of the computer to another.

Computers can be generally classified by size and power as follows, though there is considerable overlap:

*personal computer : A small, single-user computer based on a microprocessor. In addition to the microprocessor, a personal computer has a keyboard for entering data, a monitor for displaying information, and a storage device for saving data.
*workstation : A powerful, single-user computer. A workstation is like a personal computer, but it has a more powerful microprocessor and a higher-quality monitor.
*minicomputer : A multi-user computer capable of supporting from 10 to hundreds of users simultaneously.
*mainframe : A powerful multi-user computer capable of supporting many hundreds or thousands of users simultaneously.
*supercomputer : An extremely fast computer that can perform hundreds of millions of instructions per second.

Answer 3

Computer [is]
1. A set electronic appliance which can accept and process data by using a[n on file program [in] computer memory later;then give result of processing in the form of output
2. A program electronic appliance which can to data process and make calculation and process symbol ( device, picture
3. A[N functioning electronic appliance as a means of [count/calculate] and data processing which each other cooperating and consist of input appliance, output appliance and media
possible all above meaning have different sentence and word but have [is] same meaning
And have many usefulness.

Answer 4

for manipulating data according to a list of instructions known as a program.

Computers are extremely versatile. In fact, they are universal information-processing machines. According to the Church–Turing thesis, a computer with a certain minimum threshold capability is in principle capable of performing the tasks of any other computer, from those of a personal digital assistant to a supercomputer, as long as time and memory capacity are not considerations. Therefore, the same computer designs may be adapted for tasks ranging from processing company payrolls to controlling unmanned spaceflights. Due to technological advancement, modern electronic computers are exponentially more capable than those of preceding generations (a phenomenon partially described by Moore's Law).

Computers take numerous physical forms. Early electronic computers were the size of a large room, and such enormous computing facilities still exist for specialized scientific computation — supercomputers — and for the transaction processing requirements of large companies, generally called mainframes. Smaller computers for individual use, called personal computers, and their portable equivalent, the laptop computer, are ubiquitous information-processing and communication tools and are perhaps what most non-experts think of as "a computer". However, the most common form of computer in use today is the embedded computer, small computers used to control another device. Embedded computers control machines from fighter aircraft to digital cameras.

Answer 5

1. electronic data processor and storer: an electronic device that accepts, processes, stores, and outputs data at high speeds according to programmed instructions
2. somebody who computes: a person who calculates numbers or amounts using a machine

Answer 6

A device or organization and storage that provides millions of jobs in our economy

Used for a
*music machine
*dvd player
*dvd copier
*cd player
*cd copier
*tv screen
*Picture viewer
*Picture editor
*The Internet

Answer 7

I highly recommend you to surf to...
http:// en.wikipedia.org/wiki/Computer

OR type the following into google.com to find your answer.

define: computer

Answer 8

A computer is a machine for manipulating data according to a list of instructions known as a program.

Computers are extremely versatile. In fact, they are universal information-processing machines. According to the Church–Turing thesis, a computer with a certain minimum threshold capability is in principle capable of performing the tasks of any other computer, from those of a personal digital assistant to a supercomputer, as long as time and memory capacity are not considerations. Therefore, the same computer designs may be adapted for tasks ranging from processing company payrolls to controlling unmanned spaceflights. Due to technological advancement, modern electronic computers are exponentially more capable than those of preceding generations (a phenomenon partially described by Moore's Law).

Computers take numerous physical forms. Early electronic computers were the size of a large room, and such enormous computing facilities still exist for specialized scientific computation — supercomputers — and for the transaction processing requirements of large companies, generally called mainframes. Smaller computers for individual use, called personal computers, and their portable equivalent, the laptop computer, are ubiquitous information-processing and communication tools and are perhaps what most non-experts think of as "a computer". However, the most common form of computer in use today is the embedded computer, small computers used to control another device. Embedded computers control machines from fighter aircraft to digital cameras.



History of computing
Originally, the term "computer" referred to a person who performed numerical calculations, often with the aid of a mechanical calculating device or analog computer. Examples of these early devices, the ancestors of the computer, included the abacus and the Antikythera mechanism, an ancient Greek device for calculating the movements of planets, dating from about 87 BC.[1] The end of the Middle Ages saw a reinvigoration of European mathematics and engineering, and Wilhelm Schickard's 1623 device was the first of a number of European engineers to construct a mechanical calculator.[2] The abacus has been noted as being an early computer, as it was like a calculator in the past.

In 1801, Joseph Marie Jacquard made an improvement to existing loom designs that used a series of punched paper cards as a program to weave intricate patterns. The resulting Jacquard loom is not considered a true computer but it was an important step in the development of modern digital computers.

Charles Babbage was the first to conceptualize and design a fully programmable computer as early as 1820, but due to a combination of the limits of the technology of the time, limited finance, and an inability to resist tinkering with his design, the device was never actually constructed in his lifetime. A number of technologies that would later prove useful in computing, such as the punch card and the vacuum tube had appeared by the end of the 19th century, and large-scale automated data processing using punch cards was performed by tabulating machines designed by Hermann Hollerith.

During the first half of the 20th century, many scientific computing needs were met by increasingly sophisticated, special-purpose analog computers, which used a direct mechanical or electrical model of the problem as a basis for computation. These became increasingly rare after the development of the programmable digital computer.

A succession of steadily more powerful and flexible computing devices were constructed in the 1930s and 1940s, gradually adding the key features of modern computers, such as the use of digital electronics (largely invented by Claude Shannon in 1937)[3] and more flexible programmability. Defining one point along this road as "the first digital electronic computer" is exceedingly difficult. Notable achievements include the Atanasoff-Berry Computer (1937), a special-purpose machine that used valve-driven (vacuum tube) computation, binary numbers, and regenerative memory; the secret British Colossus computer (1944), which had limited programmability but demonstrated that a device using thousands of valves could be made reliable and reprogrammed electronically; the Harvard Mark I, a large-scale electromechanical computer with limited programmability (1944); the decimal-based American ENIAC (1946) — which was the first general purpose electronic computer, but originally had an inflexible architecture that meant reprogramming it essentially required it to be rewired; and Konrad Zuse's Z machines, with the electromechanical Z3 (1941) being the first working machine featuring automatic binary arithmetic and feasible programmability.

The team who developed ENIAC, recognizing its flaws, came up with a far more flexible and elegant design, which has become known as the Von Neumann architecture (or "stored program architecture"). This stored program architecture became the basis for virtually all modern computers. A number of projects to develop computers based on the stored program architecture commenced in the mid to late-1940s; the first of these were completed in Britain. The first to be up and running was the Small-Scale Experimental Machine, but the EDSAC was perhaps the first practical version that was developed.

Valve (tube) driven computer designs were in use throughout the 1950s, but were eventually replaced with transistor-based computers, which were smaller, faster, cheaper, and much more reliable, thus allowing them to be commercially produced, in the 1960s. By the 1970s, the adoption of integrated circuit technology had enabled computers to be produced at a low enough cost to allow individuals to own a personal computer.


How computers work: the stored program architecture
While the technologies used in computers have changed dramatically since the first electronic, general-purpose computers of the 1940s, most still use the stored program architecture (sometimes called the von Neumann architecture). The design made the universal computer a practical reality.

The architecture describes a computer with four main sections: the arithmetic and logic unit (ALU), the control circuitry, the memory, and the input and output devices (collectively termed I/O). These parts are interconnected by bundles of wires (called "buses" when the same bundle supports more than one data path) and are usually driven by a timer or clock (although other events could drive the control circuitry).

Conceptually, a computer's memory can be viewed as a list of cells. Each cell has a numbered "address" and can store a small, fixed amount of information. This information can either be an instruction, telling the computer what to do, or data, the information which the computer is to process using the instructions that have been placed in the memory. In principle, any cell can be used to store either instructions or data.

The ALU is in many senses the heart of the computer. It is capable of performing two classes of basic operations. The first is arithmetic operations; for instance, adding or subtracting two numbers together. The set of arithmetic operations may be very limited; indeed, some designs do not directly support multiplication and division operations (instead, users support multiplication and division through programs that perform multiple additions, subtractions, and other digit manipulations). The second class of ALU operations involves comparison operations: given two numbers, determining if they are equal, or if not equal which is larger.

The I/O systems are the means by which the computer receives information from the outside world, and reports its results back to that world. On a typical personal computer, input devices include objects like the keyboard and mouse, and output devices include computer monitors, printers and the like, but as will be discussed later a huge variety of devices can be connected to a computer and serve as I/O devices.

The control system ties this all together. Its job is to read instructions and data from memory or the I/O devices, decode the instructions, providing the ALU with the correct inputs according to the instructions, "tell" the ALU what operation to perform on those inputs, and send the results back to the memory or to the I/O devices. One key component of the control system is a counter that keeps track of what the address of the current instruction is; typically, this is incremented each time an instruction is executed, unless the instruction itself indicates that the next instruction should be at some other location (allowing the computer to repeatedly execute the same instructions).

Since the 1980s the ALU and control unit (collectively called a central processing unit or CPU) have typically been located on a single integrated circuit called a microprocessor.

The functioning of such a computer is in principle quite straightforward. Typically, on each clock cycle, the computer fetches instructions and data from its memory. The instructions are executed, the results are stored, and the next instruction is fetched. This procedure repeats until a halt instruction is encountered.

The set of instructions interpreted by the control unit, and executed by the ALU, are limited in number, precisely defined, and very simple operations. Broadly, they fit into one or more of four categories: 1) moving data from one location to another (an example might be an instruction that "tells" the CPU to "copy the contents of memory cell 5 and place the copy in cell 10"). 2) executing arithmetic and logical processes on data (for instance, "add the contents of cell 7 to the contents of cell 13 and place the result in cell 20"). 3) testing the condition of data ("if the contents of cell 999 are 0, the next instruction is at cell 30"). 4) altering the sequence of operations (the previous example alters the sequence of operations, but instructions such as "the next instruction is at cell 100" are also standard).

Instructions, like data, are represented within the computer as binary code — a base two system of counting. For example, the code for one kind of "copy" operation in the Intel x86 line of microprocessors is 10110000 [4]. The particular instruction set that a specific computer supports is known as that computer's machine language. Using an already-popular machine language makes it much easier to run existing software on a new machine; consequently, in markets where commercial software availability is important suppliers have converged on one or a very small number of distinct machine languages.

Larger computers, such as some minicomputers, mainframe computers, servers, differ from the model above in one significant aspect; rather than one CPU they often have a number of them. Supercomputers often have highly unusual architectures significantly different from the basic stored-program architecture, sometimes featuring thousands of CPUs, but such designs tend to be useful only for specialized tasks. At the other end of the size scale, some microcontrollers use the Harvard architecture that ensures that program and data memory are logically separate

Digital circuits
The conceptual design above could be implemented using a variety of different technologies. As previously mentioned, a stored program computer could be designed entirely of mechanical components like Babbage's. However, digital circuits allow Boolean logic and arithmetic using binary numerals to be implemented using relays — essentially, electrically controlled switches. Shannon's famous thesis showed how relays could be arranged to form units called logic gates, implementing simple Boolean operations. Others soon figured out that vacuum tubes — electronic devices, could be used instead. Vacuum tubes were originally used as a signal amplifier for radio and other applications, but were used in digital electronics as a very fast switch; when electricity is provided to one of the pins, current can flow through between the other two.

Through arrangements of logic gates, one can build digital circuits to do more complex tasks, for instance, an adder, which implements in electronics the same method — in computer terminology, an algorithm — to add two numbers together that children are taught — add one column at a time, and carry what's left over. Eventually, through combining circuits together, a complete ALU and control system can be built up. This does require a considerable number of components. CSIRAC, one of the earliest stored-program computers, is probably close to the smallest practically useful design. It had about 2,000 valves, some of which were "dual components"[5], so this represented somewhere between 2,000 and 4,000 logic components.

Vacuum tubes had severe limitations for the construction of large numbers of gates. They were expensive, unreliable (particularly when used in such large quantities), took up a lot of space, and used a lot of electrical power, and, while incredibly fast compared to a mechanical switch, had limits to the speed at which they could operate. Therefore, by the 1960s they were replaced by the transistor, a new device which performed the same task as the tube but was much smaller, faster operating, reliable, used much less power, and was far cheaper.


Integrated circuits are the basis of modern digital computing hardware.In the 1960s and 1970s, the transistor itself was gradually replaced by the integrated circuit, which placed multiple transistors (and other components) and the wires connecting them on a single, solid piece of silicon. By the 1970s, the entire ALU and control unit, the combination becoming known as a CPU, were being placed on a single "chip" called a microprocessor. Over the history of the integrated circuit, the number of components that can be placed on one has grown enormously. The first IC's contained a few tens of components; as of 2006, the Intel Core Duo processor contains 151 million transistors.[6]

Tubes, transistors, and transistors on integrated circuits can be used as the "storage" component of the stored-program architecture, using a circuit design known as a flip-flop, and indeed flip-flops are used for small amounts of very high-speed storage. However, few computer designs have used flip-flops for the bulk of their storage needs. Instead, earliest computers stored data in Williams tubes — essentially, projecting some dots on a TV screen and reading them again, or mercury delay lines where the data was stored as sound pulses traveling slowly (compared to the machine itself) along long tubes filled with mercury. These somewhat ungainly but effective methods were eventually replaced by magnetic memory devices, such as magnetic core memory, where electrical currents were used to introduce a permanent (but weak) magnetic field in some ferrous material, which could then be read to retrieve the data. Eventually, DRAM was introduced. A DRAM unit is a type of integrated circuit containing huge banks of an electronic component called a capacitor which can store an electrical charge for a period of time. The level of charge in a capacitor could be set to store information, and then measured to read the information when required.


I/O devices
I/O (short for input/output) is a general term for devices that send computers information from the outside world and that return the results of computations. These results can either be viewed directly by a user, or they can be sent to another machine, whose control has been assigned to the computer: In a robot, for instance, the controlling computer's major output device is the robot itself.

The first generation of computers were equipped with a fairly limited range of input devices. A punch card reader, or something similar, was used to enter instructions and data into the computer's memory, and some kind of printer, usually a modified teletype, was used to record the results. Over the years, other devices have been added. For the personal computer, for instance, keyboards and mice are the primary ways people directly enter information into the computer; and monitors are the primary way in which information from the computer is presented back to the user, though printers, speakers, and headphones are common, too. There is a huge variety of other devices for obtaining other types of input. One example is the digital camera, which can be used to input visual information. There are two prominent classes of I/O devices. The first class is that of secondary storage devices, such as hard disks, CD-ROMs, key drives and the like, which represent comparatively slow, but high-capacity devices, where information can be stored for later retrieval; the second class is that of devices used to access computer networks. The ability to transfer data between computers has opened up a huge range of capabilities for the computer. The global Internet allows millions of computers to transfer information of all types between each other.

Programs
Computer programs are simply lists of instructions for the computer to execute. These can range from just a few instructions which perform a simple task, to a much more complex instruction list which may also include tables of data. Many computer programs contain millions of instructions, and many of those instructions are executed repeatedly. A typical modern PC (in the year 2005) can execute around 3 billion instructions per second. Computers do not gain their extraordinary capabilities through the ability to execute complex instructions. Rather, they do millions of simple instructions arranged by people known as programmers.

In practice, people do not normally write the instructions for computers directly in machine language. Such programming is time-consuming and error-prone, making programmers less productive. Instead, programmers describe the desired actions in a "high level" programming language which is then translated into the machine language automatically by special computer programs (interpreters and compilers). Some programming languages map very closely to the machine language, such as Assembly Language (low level languages); at the other end, languages like Prolog are based on abstract principles far removed from the details of the machine's actual operation (high level languages). The language chosen for a particular task depends on the nature of the task, the skill set of the programmers, tool availability and, often, the requirements of the customers (for instance, projects for the US military were often required to be in the Ada programming language).

Computer software is an alternative term for computer programs; it is a more inclusive phrase and includes all the ancillary material accompanying the program needed to do useful tasks. For instance, a video game includes not only the program itself, but also data representing the pictures, sounds, and other material needed to create the virtual environment of the game. A computer application is a piece of computer software provided to many computer users, often in a retail environment. The stereotypical modern example of an application is perhaps the office suite, a set of interrelated programs for performing common office tasks.

Going from the extremely simple capabilities of a single machine language instruction to the myriad capabilities of application programs means that many computer programs are extremely large and complex. A typical example is Windows XP, created from roughly 40 million lines of computer code in the C++ programming language;[7] there are many projects of even bigger scope, built by large teams of programmers. The management of this enormous complexity is key to making such projects possible; programming languages, and programming practices, enable the task to be divided into smaller and smaller subtasks until they come within the capabilities of a single programmer in a reasonable period.

Nevertheless, the process of developing software remains slow, unpredictable, and error-prone; the discipline of software engineering has attempted, with some success, to make the process quicker and more productive and improve the quality of the end product

Libraries and operating systems
Soon after the development of the computer, it was discovered that certain tasks were required in many different programs; an early example was computing some of the standard mathematical functions. For the purposes of efficiency, standard versions of these were collected in libraries and made available to all who required them. A particularly common task set related to handling the gritty details of "talking" to the various I/O devices, so libraries for these were quickly developed.

By the 1960s, with computers in wide industrial use for many purposes, it became common for them to be used for many different jobs within an organization. Soon, special software to automate the scheduling and execution of these many jobs became available. The combination of managing "hardware" and scheduling jobs became known as the "operating system"; the classic example of this type of early operating system was OS/360 by IBM.[8]

The next major development in operating systems was timesharing — the idea that multiple users could use the machine "simultaneously" by keeping all of their programs in memory, executing each user's program for a short time so as to provide the illusion that each user had their own computer. Such a development required the operating system to provide each user's programs with a "virtual machine" such that one user's program could not interfere with another's (by accident or design). The range of devices that operating systems had to manage also expanded; a notable one was hard disks; the idea of individual "files" and a hierarchical structure of "directories" (now often called folders) greatly simplified the use of these devices for permanent storage. Security access controls, allowing computer users access only to files, directories and programs they had permissions to use, were also common.

Perhaps the last major addition to the operating system were tools to provide programs with a standardized graphical user interface. While there are few technical reasons why a GUI has to be tied to the rest of an operating system, it allows the operating system vendor to encourage all the software for their operating system to have a similar looking and acting interface.

Outside these "core" functions, operating systems are usually shipped with an array of other tools, some of which may have little connection with these original core functions but have been found useful by enough customers for a provider to include them. For instance, Apple's Mac OS X ships with a digital video editor application.

Operating systems for smaller computers may not provide all of these functions. The operating systems for early microcomputers with limited memory and processing capability did not, and Embedded computers typically have specialized operating systems or no operating system at all, with their custom application programs performing the tasks that might otherwise be delegated to an operating system

Computer applications

Computer-controlled robots are now common in industrial manufacture.
Computer-generated imagery (CGI) is a central ingredient in motion picture visual effects. The seawater creature in The Abyss (1989) marked the acceptance of CGI in the visual effects industry.
Many modern, mass-produced toys like Furby would not be possible without low-cost embedded computers.The first digital computers, with their large size and cost, mainly performed scientific calculations, often to support military objectives. The ENIAC was originally designed to calculate ballistics-firing tables for artillery, but it was also used to calculate neutron cross-sectional densities to help in the design of the hydrogen bomb,[9][10] significantly speeding up its development. (Many of the most powerful supercomputers available today are also used for nuclear weapons simulations.) The CSIR Mk I, the first Australian stored-program computer, was amongst many other tasks used for the evaluation of rainfall patterns for the catchment area of the Snowy Mountains Scheme, a large hydroelectric generation project[11] Others were used in cryptanalysis, for example the first programmable (though not general-purpose) digital electronic computer, Colossus, built in 1943 during World War II. Despite this early focus of scientific and military engineering applications, computers were quickly used in other areas.

From the beginning, stored program computers were applied to business problems. The LEO, a stored program-computer built by J. Lyons and Co. in the United Kingdom, was operational and being used for inventory management and other purposes 3 years before IBM built their first commercial stored-program computer. Continual reductions in the cost and size of computers saw them adopted by ever-smaller organizations. Moreover, with the invention of the microprocessor in the 1970s, it became possible to produce inexpensive computers. In the 1980s, personal computers became popular for many tasks, including book-keeping, writing and printing documents, calculating forecasts and other repetitive mathematical tasks involving spreadsheets.

As computers have become less expensive, they have been used extensively in the creative arts as well. Sound, still pictures, and video are now routinely created (through synthesizers, computer graphics and computer animation), and near-universally edited by computer. They have also been used for entertainment, with the video game becoming a huge industry.

Computers have been used to control mechanical devices since they became small and cheap enough to do so; indeed, a major spur for integrated circuit technology was building a computer small enough to guide the Apollo missions[12][13] two of the first major applications for embedded computers. Today, it is almost rarer to find a powered mechanical device not controlled by a computer than to find one that is at least partly so. Perhaps the most famous computer-controlled mechanical devices are robots, machines with more-or-less human appearance and some subset of their capabilities. Industrial robots have become commonplace in mass production, but general-purpose human-like robots have not lived up to the promise of their fictional counterparts and remain either toys or research projects.

Robotics, indeed, is the physical expression of the field of artificial intelligence, a discipline whose exact boundaries are fuzzy but to some degree involves attempting to give computers capabilities that they do not currently possess but humans do. Over the years, methods have been developed to allow computers to do things previously regarded as the exclusive domain of humans — for instance, "read" handwriting, play chess, or perform symbolic integration. However, progress on creating a computer that exhibits "general" intelligence comparable to a human has been extremely slow.


Networking and the Internet
Computers have been used to coordinate information in multiple locations since the 1950s, with the US military's SAGE system the first large-scale example of such a system, which led to a number of special-purpose commercial systems like Sabre.

In the 1970s, computer engineers at research institutions throughout the US began to link their computers together using telecommunications technology. This effort was funded by ARPA, and the computer network that it produced was called the ARPANET. The technologies that made the Arpanet possible spread and evolved. In time, the network spread beyond academic and military institutions and became known as the Internet. The emergence of networking involved a redefinition of the nature and boundaries of the computer. In the phrase of John Gage and Bill Joy (of Sun Microsystems), "the network is the computer". Computer operating systems and applications were modified to include the ability to define and access the resources of other computers on the network, such as peripheral devices, stored information, and the like, as extensions of the resources of an individual computer. Initially these facilities were available primarily to people working in high-tech environments, but in the 1990s the spread of applications like e-mail and the World Wide Web, combined with the development of cheap, fast networking technologies like Ethernet and ADSL saw computer networking become ubiquitous almost everywhere. In fact, the number of computers that are networked is growing phenomenally. A very large proportion of personal computers regularly connect to the Internet to communicate and receive information.[14] "Wireless" networking, often utilizing mobile phone networks, has meant networking is becoming increasingly ubiquitous even in mobile computing environments.


Alternative computing models
Despite the massive gains in speed and capacity over the history of the digital computer, there are many tasks for which current computers are inadequate. For some of these tasks, conventional computers are fundamentally inadequate, because the time taken to find a solution grows very quickly as the size of the problem to be solved expands. Therefore, there has been research interest in some computer models that use biological processes, or the oddities of quantum physics, to tackle these types of problems. For instance, DNA computing is proposed to use biological processes to solve certain problems. Because of the exponential division of cells, a DNA computing system could potentially tackle a problem in a massively parallel fashion. However, such a system is limited by the maximum practical mass of DNA that can be handled.

Quantum computers, as the name implies, take advantage of the unusual world of quantum physics. If a practical quantum computer is ever constructed, there are a limited number of problems for which the quantum computer is fundamentally faster than a standard computer. However, these problems, relating to cryptography and, unsurprisingly, quantum physics simulations, are of considerable practical interest.

These alternative models for computation remain research projects at the present time, and will likely find application only for those problems where conventional computers are inadequate


Computing professions and disciplines
In the developed world, virtually every profession makes use of computers. However, certain professional and academic disciplines have evolved that specialize in techniques to construct, program, and use computers. Terminology for different professional disciplines is still somewhat fluid and new fields emerge from time to time: however, some of the major groupings are as follows:

Computer engineering is the branch of electrical engineering that focuses both on hardware and software design, and the interaction between the two.
Computer science is an academic study of the processes related to computation, such as developing efficient algorithms to perform specific tasks. It tackles questions as to whether problems can be solved at all using a computer, how efficiently they can be solved, and how to construct efficient programs to compute solutions. A huge array of specialties has developed within computer science to investigate different classes of problems.
Software engineering concentrates on methodologies and practices to allow the development of high quality software systems, while minimizing, and reliably estimating, costs and timelines.
Information systems concentrates on the use and deployment of computer systems in a wider organizational (usually business) context.
Many disciplines have developed at the intersection of computers with other professions; one of many examples is experts in geographical information systems who apply computer technology to problems of managing geographical information.
There are two major professional societies dedicated to computers, the Association for Computing Machinery and IEEE Computer Society.



Analog Computer
An analog computer is a form of computer that uses electrical or mechanical phenomena to model the problem being solved by using one kind of physical quantity to represent another. The central concept among all analog computers can be better understood by examining the definition of an analogy. The similarities of an analogy define the salient characteristics of the comparison, but the differences in an analogy are also important. Modeling a real physical system in a computer is called simulation.

For example, the similarity between linear mechanical components, such as springs and dashpots, and electrical components, such as capacitors, inductors, and resistors is striking in terms of mathematics, or even direct mapping as in simulation. They can be modeled using equations that are of the same form. Other methods include direct observation without the aid of mathematics. For example, water pressure can be simulated by voltage and water flow in terms of gallons per minute can be simulated by amperes.

However, the difference between these systems is what makes analog computing useful. If one considers a simple mass-spring system, constructing the physical system would require buying the springs and masses. This would be proceeded by attaching them to each other and an appropriate anchor, collecting test equipment with the appropriate input range, and finally, taking (somewhat difficult) measurements.

The electrical equivalent can be constructed with a few operational amplifiers (Op amps) and some passive linear components; all measurements can be taken directly with an oscilloscope. In the circuit, the (simulated) 'mass of the spring' can be changed by adjusting a potentiometer. The electrical system is an analogy to the physical system, hence the name, but it is less expensive to construct, safer, and easier to modify. The all-electronic analog computer is also extremely fast, since a calculation is completed at the rate at which a signal traverses the circuit, which is generally an appreciable fraction of the speed of light.

The drawback of the mechanical-electrical analogy is that electronics are limited by the range over which the variables may vary. This is called dynamic range. They are also limited by noise levels.

There is a lack of understanding about electrical systems that sometimes leads to the terms analog and digital having seemingly confusing and somewhat dubious meanings. Analog systems are sometimes understood only as continuous, time variant electrical systems. From the above discussion this is not correct, since discontinuous functions may also be modeled. In fact, digital also has a precise technical definition. In the context of circuits, it refers to the use of discrete electrical voltage levels as codes for symbols and the manipulation of these symbols in the operation of the digital computer. The electronic analog computer manipulates the physical quantities of (waveforms) of volts or amperes. Consequently, the precision of the analog computer readout (of rational numbers) is limited only by the quantization of the readout equipment used (generally three or four places). The digital computer precision must necessarily be finite, but the precision of its result is limited only by time.

There is an intermediate device, a hybrid computer, in which a digital computer is combined with an analog computer. Hybrid computers are used to obtain a very accurate but imprecise 'seed' value, using an analog computer front-end, which is then fed into a digital computer iterative process to achieve the final desired degree of precision. With a three or four digit, highly accurate numerical seed, the total digital computation time necessary to reach the desired precision is dramatically reduced, since many fewer iterations are required. Or, for example, the analog computer might be used to solve a non-analytic differential equation problem for use at some stage of an overall computation (where precision is not very important). In any case, the hybrid computer is usually substantially faster than a digital computer, but can supply a far more precise computation than an analog computer. It is useful for real-time applications requiring such a combination (e.g., a high frequency phased-array radar or a weather system computation).


Chemical Computer
A chemical computer, also called reaction-diffusion computer, BZ computer or gooware computer is an unconventional computer based on a semi-solid chemical "soup" where data is represented by varying concentrations of chemicals. The computations are performed by naturally occurring chemical reactions. So far it is still in a very early experimental stage, but may have great potential for the computer industry

DNA Computer
DNA computing is a form of computing which uses DNA and molecular biology, instead of the traditional silicon-based computer technologies.

This field was initially developed by Leonard Adleman of the University of Southern California. In 1994, Adleman demonstrated a proof-of-concept use of DNA as form of computation which was used to solve the seven-point Hamiltonian path problem. Since the initial Adleman experiments, advances have been made, and various Turing machines have been proven to be constructable.

There are works over one dimensional lengths, bidimensional tiles, and even three dimensional DNA graphs processing.

On April 28, 2004, Ehud Shapiro and researchers at the Weizmann Institute announced in the journal Nature that they had constructed a DNA computer. This was coupled with an input and output module and is capable of diagnosing cancerous activity within a cell, and then releasing an anti-cancer drug upon diagnosis.

DNA computing is fundamentally similar to parallel computing in that it takes advantage of the many different molecules of DNA to try many different possibilities at once.

For certain specialized problems, DNA computers are faster and smaller than any other computer built so far. But DNA computing does not provide any new capabilities from the standpoint of computational complexity theory, the study of which computational problems are difficult. For example, problems which grow exponentially with the size of the problem (EXPSPACE problems) on von Neumann machines still grow exponentially with the size of the problem on DNA machines. For very large EXPSPACE problems, the amount of DNA required is too large to be practical. (Quantum computing, on the other hand, does provide some interesting new capabilities).


Molecular Computer
Molecular computers are massively parallel computers taking advantage of the compuational power of molecules

Optical Computer
An optical computer is a computer that uses bound electrons in isolating crystals instead of free electrons in transistors for computation. Its digital signals are modulated onto a carrier wave in the visible region. No modulator or demodulator exists, because the base band offers only 10 GHz bandwidth whereas the visible band offers 10 THz. It is like doing digital computation by a radio.

One fundamental limit is the size. Optical fibres on an integrated optic chip are ten times wider than the traces on an integrated electronics circuit chip. The crystals have the same cross-section as the fibres, but need a length of about 1 mm and so are much larger than a transistor. Therefore signal traveling times will be large.

A more practical limit is the crystal. Current crystals need light with 1 GW/cm² intensity. And as a typical die (in microelectronics) is about 1 cm², and some absorption takes place, this means kilowatts of power consumption, which only allows pulsed operation, but nanotubes may reduce this in the future.

The biggest advantage in the near future is the synergy with optical telecommunication.

It performs its computation with photons or polaritons as opposed to the more traditional electron-based computation. Optical computing is a major branch of the study of photonics and polaritonics. Electronics computations sometimes involve communications via photonic pathways. Popular devices of this class include FDDI interfaces. In order to send the information via photons, electronic signals are converted via lasers and the light guided down the optical fiber.

No true optical computers are declassified or otherwise known to exist. Some devices that are best classified as switches have been tested in the laboratory. Transistors that are composed entirely of optical components are themselves still very new and experimental.

A fully functional computer is composed of many transistors. The number of them required to constitute a computer is arguable, but probably at least 10 and more often 1,000,000 transistors are required to do general computing tasks.

Currently, no true optical computers yet exist. The problems of design seem to stem from eliminating the conversion from photons to electrons and back. This conversion is necessary now because we don't have all-optical versions of all the myriad switching devices required by a computer.

An interesting property of optical computers, optical pathways- is they can carry many different frequencies of light over each pathway and the light detector(s) can be filtered to respond to each of those frequencies, depending on the flexibly programmed topology used. Very Large arrays (VLA's) (4 megapixels and above) can be fabricated like large optical arrays, each passing, switching or filtering each of the various frequency laser beams.
Iteration can be accomplished by feedback, as in gate arrays, where the output is fed into different inputs to provide greater programmed logic combinations. Light pathways can exist in many layers of adjacent silicon by total internal light guide reflection as in fiber optics, except reflection of the beams are in many parallel vertical and horizontal lightguide pathways in the bulk silicon substrate, created by AutoCAD like step and repeat programmed layout wafer fabrication lightguide pathways.
Crossover switches are used to switch the light beam onto a new light pathway(s), can be accomplished by optical banyan switches, using non-linear optics or MEMS mirrors to steer a light beam onto or off of its intended path. These are used currently in optical switches for fiber optics. A 2000 x 2000 switch can be used for 4 million pathways, with 4 Mpixel CCDs used as the light detector(s) as in digital cameras, to convert the binary(on-off light) back into the electrical from the photonic realm. Silicon dioxide is glass-like and is transparent to lasers. The input(s) is/are a very large array of VCSELs lasers.
Beam-splitters and mirrors move the light up/down or left/right in the array by silicon being placed at 45 degree angles like these symbols left or up "/" or right or down "\" or straight through "-" or reflecting "|". Periscopes use these same principle, only these are very large microminiature stacked arrays on silicon substrate, using a few more micrometres of depth for the additional array layouts. Putting a combination of these pathways in stacked interconnected multi-layer VLArrays, with banyan switches (to re-program any one pathway onto another) at the output or CCD detector, before being fedback into the optical inputs, allows more programming combinations, and general programming schemes to be employed in a massively parallel optical computer. refs: SAI1992, OAO, SPIE, Photonics Magazine.
Many different clock cycles are possible, both async and synchronously at the same time by using different wavelengths for each clock on the same lightguide pathway. Combinoral logic can be used with the presence or absence or each clock color. This can give rise to more complex functions. The need for more clocks becomes apparent with massively parallel independent sectored processors.
Optical Computing has the main advantages of small size/high density, high speed, low heating of junctions and substrate, dynamically reconfigurable, scalable into larger/smaller topologies/networks, well matched for imaging, massively parallel computing capability and artificial intelligence applications—i.e., neural networks of great complexity.
The future of computing is leaning towards large parallel arrays using photonics, rather than electronics, but will probably be for all practical purposes, be opto-electronic in nature, due to the current realm of electronic computing prevalence of using representative voltages to denote "0" or "1" binary states. Optical computing uses a direct analogy of presence or absence of the recognized signal medium, many laser frequencies on a single optical pathway. Multiplexing many frequencies of laser light onto and de-multiplexing off of an optical pathway are common place in DWDM fiber optics for long haul data transfers between cities at 10 to 40 Gbit/s. Thin films on surfaces can make excellent filters of light or polarization.
Interestingly, modern (normal) electronic computers are taking on significant radio wave properties by themselves. Since the frequency of the system clocks on fast systems has passed the single gigahertz range, circuit designers must consider that any electronic signal varying at such rates will be giving off radio waves at that frequency. This means that a wire in a computer performs the dual function of a conductor of electricity and a waveguide for a gigahertz frequency radio wave.


Quantum Computer
A quantum computer is any device for computation that makes direct use of distinctively quantum mechanical phenomena, such as superposition and entanglement, to perform operations on data. In a classical (or conventional) computer, the amount of data is measured by bits; in a quantum computer, it is measured by qubits. The basic principle of quantum computation is that the quantum properties of particles can be used to represent and structure data, and that quantum mechanisms can be devised and built to perform operations with this data.1

Though quantum computing is still in its infancy, experiments have been carried out in which quantum computational operations were executed on a very small number of qubits. Research in both theoretical and practical areas continues at a frantic pace, and many national government and military funding agencies support quantum computing research, to develop quantum computers for both civilian and national security purposes, such as cryptanalysis. 2 (See Timeline of quantum computing for details on current and past progress.)

It is widely believed that if large-scale quantum computers can be built, they will be able to solve certain problems faster than any classical computer. Quantum computers are different from classical computers such as DNA computers and computers based on transistors, even though these may ultimately use some kind of quantum mechanical effect (for example covalent bonds). Some computing architectures such as optical computers may use classical superposition of electromagnetic waves, but without some specifically quantum mechanical resource such as entanglement, they do not share the potential for computational speed-up of quantum computers.

Wetware Computer
A wetware computer is an organic computer (also known as an artificial organic brain or a neurocomputer) built from living neurons. Professor Bill Ditto, at the Georgia Institute of Technology, is the primary researcher driving the creation of these artificially constructed, but still organic brains. One prototype is constructed from leech neurons, and is capable of performing simple arithmetic operations. The concepts are still being researched and prototyped, but in the near future, it is expected that artificially constructed organic brains, even though they are still considerably simpler in design than Darwinian-evolved animal brains, should be capable of simple pattern recognition tasks such as handwriting recognition

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