Saturday, August 23, 2008

super computer


A supercomputer is a computer that is at the frontline of processing capacity, particularly speed of calculation (at the time of its introduction). The term "Super Computing" was first used by New York World newspaper in 1929[1] to refer to large custom-built tabulators that IBM had made for Columbia University.
Supercomputers introduced in the 1960s were designed primarily by Seymour Cray at Control Data Corporation (CDC), and led the market into the 1970s until Cray left to form his own company, Cray Research. He then took over the supercomputer market with his new designs, holding the top spot in supercomputing for five years (1985–1990). Cray, himself, never used the word "supercomputer"; a little-remembered fact is that he only recognized the word "computer". In the 1980s a large number of smaller competitors entered the market, in a parallel to the creation of the minicomputer market a decade earlier, but many of these disappeared in the mid-1990s "supercomputer market crash". Today, supercomputers are typically one-of-a-kind custom designs produced by "traditional" companies such as Cray, IBM and HP, who had purchased many of the 1980s companies to gain their experience.
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Common uses :
Supercomputers are used for highly calculation-intensive tasks such as problems involving quantum mechanical physics, weather forecasting, climate research (including research into global warming), molecular modeling (computing the structures and properties of chemical compounds, biological macromolecules, polymers, and crystals), physical simulations (such as simulation of airplanes in wind tunnels, simulation of the detonation of nuclear weapons, and research into nuclear fusion), cryptanalysis, and the like. Major universities, military agencies and scientific research laboratories are heavy users.
A particular class of problems, known as Grand Challenge problems, are problems whose full solution requires semi-infinite computing resources.
Relevant here is the distinction between capability computing and capacity computing, as defined by Graham et al. Capability computing is typically thought of as using the maximum computing power to solve a large problem in the shortest amount of time. Often a capability system is able to solve a problem of a size or complexity that no other computer can. Capacity computing in contrast is typically thought of as using efficient cost-effective computing power to solve somewhat large problems or many small problems or to prepare for a run on a capability system.
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Hardware and software design:
Supercomputers using custom CPUs traditionally gained their speed over conventional computers through the use of innovative designs that allow them to perform many tasks in parallel, as well as complex detail engineering. They tend to be specialized for certain types of computation, usually numerical calculations, and perform poorly at more general computing tasks. Their memory hierarchy is very carefully designed to ensure the processor is kept fed with data and instructions at all times — in fact, much of the performance difference between slower computers and supercomputers is due to the memory hierarchy. Their I/O systems tend to be designed to support high bandwidth, with latency less of an issue, because supercomputers are not used for transaction processing.
As with all highly parallel systems, Amdahl's law applies, and supercomputer designs devote great effort to eliminating software serialization, and using hardware to address the remaining bottlenecks.

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Supercomputer challenges, technologies:
A supercomputer generates large amounts of heat and must be cooled. Cooling most supercomputers is a major HVAC problem.
Information cannot move faster than the speed of light between two parts of a supercomputer. For this reason, a supercomputer that is many meters across must have latencies between its components measured at least in the tens of nanoseconds. Seymour Cray's supercomputer designs attempted to keep cable runs as short as possible for this reason: hence the cylindrical shape of his Cray range of computers. In modern supercomputers built of many conventional CPUs running in parallel, latencies of 1-5 microseconds to send a message between CPUs are typical.
Supercomputers consume and produce massive amounts of data in a very short period of time. According to Ken Batcher, "A supercomputer is a device for turning compute-bound problems into I/O-bound problems." Much work on external storage bandwidth is needed to ensure that this information can be transferred quickly and stored/retrieved correctly.
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Modern supercomputer architecture:
As of November 2006, the top ten supercomputers on the Top500 list (and indeed the bulk of the remainder of the list) have the same top-level architecture. Each of them is a cluster of MIMD multiprocessors, each processor of which is SIMD. The supercomputers vary radically with respect to the number of multiprocessors per cluster, the number of processors per multiprocessor, and the number of simultaneous instructions per SIMD processor. Within this hierarchy we have:
A computer cluster is a collection of computers that are highly interconnected via a high-speed network or switching fabric. Each computer runs under a separate instance of an Operating System (OS).
A multiprocessing computer is a computer, operating under a single OS and using more than one CPU, where the application-level software is indifferent to the number of processors. The processors share tasks using Symmetric multiprocessing (SMP) and Non-Uniform Memory Access (NUMA).
A SIMD processor executes the same instruction on more than one set of data at the same time. The processor could be a general purpose commodity processor or special-purpose vector processor. It could also be high performance processor or a low power processor. As of 2007, the processor executes several SIMD instructions per nanosecond.
As of July 2008 the fastest machine is IBM Roadrunner. This machine is a cluster of 3240 computers, each with 40 processing cores. By contrast, Columbia is a cluster of 20 machines, each with 512 processors, each of which processes two data streams concurrently.
Moore's Law and economies of scale are the dominant factors in supercomputer design: a single modern desktop PC is now more powerful than a 15-year old supercomputer, and the design concepts that allowed past supercomputers to out-perform contemporaneous desktop machines have now been incorporated into commodity PCs. Furthermore, the costs of chip development and production make it uneconomical to design custom chips for a small run and favor mass-produced chips that have enough demand to recoup the cost of production. A current model quad-core Xeon workstation running at 2.66 GHz will outperform a multimillion dollar Cray C90 supercomputer used in the early 1990s; most workloads requiring such a supercomputer in the 1990s can now be done on workstations costing less than 4,000 US dollars.
Additionally, many problems carried out by supercomputers are particularly suitable for parallelization (in essence, splitting up into smaller parts to be worked on simultaneously) and, particularly, fairly coarse-grained parallelization that limits the amount of information that needs to be transferred between independent processing units. For this reason, traditional supercomputers can be replaced, for many applications, by "clusters" of computers of standard design which can be programmed to act as one large computer.

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Current fastest supercomputer system:
On June 8, 2008, the Cell/AMD Opteron-based IBM Roadrunner at the Los Alamos National Laboratory (LANL) was announced as the fastest operational supercomputer, with a sustained processing rate of 1.026 PFLOPS.[2][3] However, Roadrunner was then taken out of service to be shipped to its new home.























DBMS

A DBMS is a complex set of software programs that controls the organization, storage, management, and retrieval of data in a database. DBMS are categorized according to their data structures or types, some time DBMS is also known as Data base Manager. It is a set of prewritten programs that are used to store, update and retrieve a Database. A DBMS includes:

A modeling language to define the schema of each database hosted in the DBMS, according to the DBMS data model.
The four most common types of organizations are the hierarchical, network, relational and object models. Inverted lists and other methods are also used. A given database management system may provide one or more of the four models. The optimal structure depends on the natural organization of the application's data, and on the application's requirements (which include transaction rate (speed), reliability, maintainability, scalability, and cost).
The dominant model in use today is the ad hoc one embedded in SQL, despite the objections of purists who believe this model is a corruption of the relational model, since it violates several of its fundamental principles for the sake of practicality and performance. Many DBMSs also support the Open Database Connectivity API that supports a standard way for programmers to access the DBMS.
Data structures (fields, records, files and objects) optimized to deal with very large amounts of data stored on a permanent data storage device (which implies relatively slow access compared to volatile main memory).
A database query language and report writer to allow users to interactively interrogate the database, analyze its data and update it according to the users privileges on data.
It also controls the security of the database.
Data security prevents unauthorized users from viewing or updating the database. Using passwords, users are allowed access to the entire database or subsets of it called subschemas. For example, an employee database can contain all the data about an individual employee, but one group of users may be authorized to view only payroll data, while others are allowed access to only work history and medical data.
If the DBMS provides a way to interactively enter and update the database, as well as interrogate it, this capability allows for managing personal databases. However, it may not leave an audit trail of actions or provide the kinds of controls necessary in a multi-user organization. These controls are only available when a set of application programs are customized for each data entry and updating function.
  • The DBMS accepts requests for data from the application program and instructs the operating system to transfer the appropriate data.
    When a DBMS is used, information systems can be changed much more easily as the organization's information requirements change. New categories of data can be added to the database without disruption to the existing system
  • DBMS benefits
    Improved strategic use of corporate data
    Reduced complexity of the organization’s information systems environment
    Reduced data redundancy and inconsistency
    Enhanced data integrity
    Application-data independence
    Reduced application development and maintenance costs
    Improved flexibility of information systems
    Increased access and availability of data and information
    Logical & Physical data independence
    Concurrent access anomalies.
    Facilitates atomicity problem.
    Provides central control on the system through DBA.



















COMPUTER SCIENCE

Computer science (or computing science) is the study and the science of the theoretical foundations of information and computation and their implementation and application in computer systems.[1][2][3] Computer science has many sub-fields; some emphasize the computation of specific results (such as computer graphics), while others relate to properties of computational problems (such as computational complexity theory). Still others focus on the challenges in implementing computations. For example, programming language theory studies approaches to describing computations, while computer programming applies specific programming languages to solve specific computational problems. A further subfield, human-computer interaction, focuses on the challenges in making computers and computations useful, usable and universally accessible to people.



Applications within computer science
A formal definition of computation and computability, and proof that there are computationally unsolvable and intractable problems.[10]
The concept of a programming language, a tool for the precise expression of methodological information at various levels of abstraction.[11]
Applications outside of computing
Sparked the Digital Revolution which led to the current Information Age and the Internet.[12]
In cryptography, breaking the Enigma machine was an important factor contributing to the Allied victory in World War II.[9]
Scientific computing enabled advanced study of the mind and mapping the human genome was possible with Human Genome Project.[12] Distributed computing projects like protein folding.
Algorithmic trading has increased the efficiency and liquidity of financial markets by using artificial intelligence, machine learning and other statistical and numerical techniques on a large scale.





Software engineering is the application of a systematic, disciplined, quantifiable approach to the development, operation, and maintenance of software.[1] It encompasses techniques and procedures, often regulated by a software development process, with the purpose of improving the reliability and maintainability of software systems.[2] The effort is necessitated by the potential complexity of those systems, which may contain millions of lines of code.[3]
The term software engineering was coined by Brian Randell and popularized by F.L. Bauer during the NATO Software Engineering Conference in 1968.[4] The discipline of software engineering includes knowledge, tools, and methods for software requirements, software desig, software construction, software testing, and software maintenance tasks.[5] Software engineering is related to the disciplines of computer science, computer engineering, management, mathematics, project management, quality management, software ergonomics, and systems engineering.[6]
In 2004, the U. S. Bureau of Labor Statistics counted 760,840 software engineers holding jobs in the U.S.; in the same time period there were some 1.4 million practitioners employed in the U.S. in all other engineering disciplines combined.[7] Due to its relative newness as a field of study, formal education in software engineering is often taught as part of a computer science curriculum, and as a result most software engineers hold computer science degrees.[8]The term software engineer is used very liberally in the corporate world. Very few of the practicing software engineers actually hold Engineering degrees from accredited universities. In fact, according to the Association for Computing Machinery, "most people who now function in the U.S. as serious software engineers have degrees in computer science, not in software engineering".

history of programming


The earliest programmable machine (that is a machine whose behavior can be controlled by changes to a "program") was Al-Jazari's programmable humanoid robot in 1206. Al-Jazari's robot was originally a boat with four automatic musicians that floated on a lake to entertain guests at royal drinking parties. His mechanism had a programmable drum machine with pegs (cams) that bump into little levers that operate the percussion. The drummer could be made to play different rhythms and different drum patterns by moving the pegs to different locaations .

The Jacquard Loom, developed in 1801, is often quoted as a source of prior art. The machine used a series of pasteboard cards with holes punched in them. The hole pattern represented the pattern that the loom had to follow in weaving cloth. The loom could produce entirely different weaves using different sets of cards. The use of punched cards was also adopted by Charles Babbage around 1830, to control his Analytical Engine.

This innovation was later refined by Herman Hollerith who, in 1896 founded the Tabulating Machine Company (which became IBM). He invented the Hollerith punched card, the cardreader, and the key punch machine. These inventions were the foundation of the modern information processing industry. The addition of a plug-board to his 1906 Type I Tabulator allowed it to do different jobs without having to be rebuilt (the first step toward programming). By the late 1940s there were a variety of plug-board programmable machines, called unit record equipment, to perform data processing tasks (card reading). The early computers were also programmed using plug-boards.
The invention of the Von Neumann architecture allowed computer programs to be stored in computer memory. Early programs had to be painstakingly crafted using the instructions of the particular machine, often in binary notation. Every model of computer would be likely to need different instructions to do the same task. Later assembly languages were developed that let the programmer specify each instruction in a text format, entering abbreviations for each operation code instead of a number and specifying addresses in symbolic form (e.g. ADD X, TOTAL). In 1954 Fortran, the first higher level programming language, was invented. This allowed programmers to specify calculations by entering a formula directly (e.g. Y = X*2 + 5*X + 9). The program text, or source, was converted into machine instructions using a special program called a compiler. Many other languages were developed, including ones for commercial programming, such as COBOL. Programs were mostly still entered using punch cards or paper tape. (See computer programming in the punch card era). By the late 1960s, data storage devices and computer terminals became inexpensive enough so programs could be created by typing directly into the computers. Text editors were developed that allowed changes and corrections to be made much more easily than with punch cards.

As time has progressed, computers have made giant leaps in the area of processing power. This has brought about newer programming languages that are more abstracted from the underlying hardware. Although these more abstracted languages require additional overhead, in most cases the huge increase in speed of modern computers has brought about little performance decrease compared to earlier counterparts. The benefits of these more abstracted languages is that they allow both an easier learning curve for people less familiar with the older lower-level programming languages, and they also allow a more experienced programmer to develop simple applications quickly. Despite these benefits, large complicated programs, and programs that are more dependent on speed still require the faster and relatively lower-level languages with today's hardware. (The same concerns were raised about the original Fortran language.)
Throughout the second half of the twentieth century, programming was an attractive career in most developed countries. Some forms of programming have been increasingly subject to offshore outsourcing (importing software and services from other countries, usually at a lower wage), making programming career decisions in developed countries more complicated, while increasing economic opportunities in less developed areas. It is unclear how far this trend will continue and how deeply it will impact programmer wages and opportunities.


























programming

Computer programming (often shortened to programming or coding), sometimes considered a branch of applied mathematics, is the process of writing, testing, debugging/troubleshooting, and maintaining the source code of computer programs. This source code is written in a programming language. The code may be a modification of an existing source or something completely new. The purpose of programming is to create a program that exhibits a certain desired behavior (customization). The process of writing source code requires expertise in many different subjects, including knowledge of the application domain, specialized algorithms and formal logic.
Said another way, programming is the craft of transforming requirements into something that a computer can execute.

Within software engineering, programming (the implementation) is regarded as one phase in a software development process.
There is an ongoing debate on the extent to which the writing of programs is an art, a craft or an engineering discipline.[1] Good programming is generally considered to be the measured application of all three, with the goal of producing an efficient and maintainable software solution (the criteria for "efficient" and "maintainable" vary considerably). The discipline differs from many other technical professions in that programmers generally do not need to be licensed or pass any standardized (or governmentally regulated) certification tests in order to call themselves "programmers" or even "software engineers".

Another ongoing debate is the extent to which the programming language used in writing programs affects the form that the final program takes. This debate is analogous to that surrounding the Sapir-Whorf hypothesis [2] in linguistics, that postulates that a particular language's nature influences the habitual thought of its speakers. Different language patterns yield different patterns of thought. This idea challenges the possibility of representing the world perfectly with language, because it acknowledges that the mechanisms of any language condition the thoughts of its speaker community





Sunday, August 17, 2008

advantage of computers in business













  1. Computers are a multimedia tool. With integrated graphic, print, audio, and video capabilities, computers can effectively link various technologies.
  2. Interactive video and CD-ROM technologies can be incorporated into computer-based instructional units. Computers are interactive

  3. Microcomputer systems incorporating various software packages are extremely flexible and maximize control.
  4. Computer technology is rapidly advancing.
  5. Innovations are constantly emerging, while related costs drop.
  6. Computers increase access. Local, regional, and national networks link resources and individuals, wherever they might be.


Computers may be the cause of technology being used wrongly e.g. fierce competition in discovery learning by undermining other people's work.

  • Computers will become inoperable due to a power failure leaving large companies at a stand still e.g. water-pumps production, vehicle making.
  • To a small extent, computers may lead to redundancy. Clerical work may become more straightforward to perform by using specially designed software.
  • Although this may happen, it never materialized to the great degree forecasted in the beginning of the 80s when the first technology boom was at its peak.









USES OF COMPUTERS IN BANKING:
E-Banking:

Electronic banking, also known as electronic fund transfer (EFT), uses computer and electronic technology as a substitute for checks and other paper transactions. ATM:
Automated Teller Machines or 24-hour Tellers are electronic terminals that let you bank almost any time. To withdraw cash, make deposits, or transfer funds between accounts, you generally insert an ATM card and enter your PIN. ATM use is increasing over the years.
DIRECT DEPOSIT:
Direct Deposit lets you authorize specific deposits, such as paychecks and Social Security checks, to your account on a regular basis. PC BANKING:
Personal Computer Banking lets you handle many banking transactions via your personal computer. You may use your computer to view your account balance, request transfers between accounts, and pay bills electronically. Point-of-Sale Transfers:
Lets you pay for purchases with a debit card, which also may be your ATM card.
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Saturday, July 5, 2008



Semiconductors are very similar to insulators. The two categories of solids differ primarily in that insulators have larger band gapsenergies that electrons must acquire to be free to move from atom to atom. In semiconductors at room temperature, just as in insulators, very few electrons gain enough thermal energy to leap the band gap from the valence band to the conduction band, which is necessary for electrons to be available for electric current conduction. For this reason, pure semiconductors and insulators in the absence of applied electric fields, have roughly similar resistance. The smaller bandgaps of semiconductors, however, allow for other means besides temperature to control their electrical properties.
Semiconductors' intrinsic electrical properties are often permanently modified by introducing impurities by a process known as doping. Usually, it is sufficient to approximate that each impurity atom adds one electron or one "hole" (a concept to be discussed later) that may flow freely. Upon the addition of a sufficiently large proportion of impurity dopants, semiconductors will conduct electricity nearly as well as metals. Depending on the kind of impurity, a doped region of semiconductor can have more electrons or holes, and is named N-type or P-type semiconductor material, respectively. Junctions between regions of N- and P-type semiconductors create electric fields, which cause electrons and holes to be available to move away from them, and this effect is critical to semiconductor device operation. Also, a density difference in the amount of impurities produces a small electric field in the region which is used to accelerate non-equilibrium electrons or holes.
In addition to permanent modification through doping, the resistance of semiconductors is normally modified dynamically by applying electric fields. The ability to control resistance/conductivity in regions of semiconductor material dynamically through the application of electric fields is the feature that makes semiconductors useful. It has led to the development of a broad range of semiconductor devices, like transistors and diodes. Semiconductor devices that have dynamically controllable conductivity, such as transistors, are the building blocks of integrated circuits devices like the microprocessor. These "active" semiconductor devices (transistors) are combined with passive components implemented from semiconductor material such as capacitors and resistors, to produce complete electronic circuits.
In most semiconductors, when electrons lose enough energy to fall from the conduction band to the valence band (the energy levels above and below the band gap), they often emit light. This photoemission process underlies the light-emitting diode (LED) and the semiconductor laser, both of which are very important commercially. Conversely, semiconductor absorption of light in photodetectors excites electrons to move from the valence band to the higher energy conduction band, thus facilitating detection of light and vary with its intensity. This is useful for fiber optic communications, and providing the basis for energy from solar cells.
Semiconductors may be elemental materials such as silicon and germanium, or compound semiconductors such as gallium arsenide and indium phosphide, or alloys such as silicon germanium or aluminium gallium arsenide.


[edit] Band structure



atoms - crystal - vacuum

In a single H-atom an electron resides in well known orbits. Note that the orbits are called s,p,d in order of increasing circular current.

Putting two atoms together leads to delocalized orbits across two atoms, a so called covalent bond. Due to Paulis principle in every state there is max one electron.

This can be continued with more atoms. Note: This picture unfortunately shows a metal.

Using 6 carbon atoms one can create molecular orbits which allow for circular current. Filling the states following Pauli's principle leads to zero net current. Current due to uneven filling needs an energy investment.

Proceeding in a regular fashion and create a crystal, which may after creation be cut into a tape and fused together at the ends allow for circular currents.

For this regular solid the band structure can be calculated or measured.

Integrating over the k axis gives the bands of a semiconductor showing a full valence band and an empty conduction band. Generally stopping at the vacuum level is dumb, because some people want to calculate: photoemission, inverse photoemission, Semiconductor_detector#particle_detectors

After the band structure is determined states can be combined to generate wave packets. As this is analogous to wave packages in free space, the results are similar.

An alternative description, which does not really appreciate the strong Coulomb interaction, shoots free electrons into the crystal and looks at the scattering.

A third alternative description uses strongly localized unpaired electrons in chemical bonds, which looks almost like a Mott insulator.

History of computing
Main article: History of computer hardware

The Jacquard loom was one of the first programmable devices.
It is difficult to identify any one device as the earliest computer, partly because the term "computer" has been subject to varying interpretations over time. Originally, the term "computer" referred to a person who performed numerical calculations (a human computer), often with the aid of a mechanical calculating device.
The history of the modern computer begins with two separate technologies - that of automated calculation and that of programmability.
Examples of early mechanical calculating devices included the abacus, the slide rule and arguably the astrolabe and the Antikythera mechanism (which dates from about 150-100 BC). The end of the Middle Ages saw a re-invigoration of European mathematics and engineering, and Wilhelm Schickard's 1623 device was the first of a number of mechanical calculators constructed by European engineers. However, none of those devices fit the modern definition of a computer because they could not be programmed.
Hero of Alexandria (c. 10 – 70 AD) built a mechanical theater which performed a play lasting 10 minutes and was operated by a complex system of ropes and drums that might be considered to be a means of deciding which parts of the mechanism performed which actions - and when.[3] This is the essence of programmability. In 1801, Joseph Marie Jacquard made an improvement to the textile loom that used a series of punched paper cards as a template to allow his loom to weave intricate patterns automatically. The resulting Jacquard loom was an important step in the development of computers because the use of punched cards to define woven patterns can be viewed as an early, albeit limited, form of programmability.
It was the fusion of automatic calculation with programmability that produced the first recognizable computers. In 1837, Charles Babbage was the first to conceptualize and design a fully programmable mechanical computer that he called "The Analytical Engine".[4] Due to limited finances, and an inability to resist tinkering with the design, Babbage never actually built his Analytical Engine.
Large-scale automated data processing of punched cards was performed for the U.S. Census in 1890 by tabulating machines designed by Herman Hollerith and manufactured by the Computing Tabulating Recording Corporation, which later became IBM. By the end of the 19th century a number of technologies that would later prove useful in the realization of practical computers had begun to appear: the punched card, Boolean algebra, the vacuum tube (thermionic valve) and the teleprinter.
During the first half of the 20th century, many scientific computing needs were met by increasingly sophisticated analog computers, which used a direct mechanical or electrical model of the problem as a basis for computation. However, these were not programmable and generally lacked the versatility and accuracy of modern digital computers.
Defining characteristics of some early digital computers of the 1940s (In the history of computing hardware)
Name
First operational
Numeral system
Computing mechanism
Programming
Turing complete
Zuse Z3 (Germany)
May 1941
Binary
Electro-mechanical
Program-controlled by punched film stock
Yes (1998)
Atanasoff–Berry Computer (USA)
Summer 1941
Binary
Electronic
Not programmable—single purpose
No
Colossus (UK)
January 1944
Binary
Electronic
Program-controlled by patch cables and switches
No
Harvard Mark I – IBM ASCC (USA)
1944
Decimal
Electro-mechanical
Program-controlled by 24-channel punched paper tape (but no conditional branch)
Yes (1998)
ENIAC (USA)
November 1945
Decimal
Electronic
Program-controlled by patch cables and switches
Yes
Manchester Small-Scale Experimental Machine (UK)
June 1948
Binary
Electronic
Stored-program in Williams cathode ray tube memory
Yes
Modified ENIAC (USA)
September 1948
Decimal
Electronic
Program-controlled by patch cables and switches plus a primitive read-only stored programming mechanism using the Function Tables as program ROM
Yes
EDSAC (UK)
May 1949
Binary
Electronic
Stored-program in mercury delay line memory
Yes
Manchester Mark I (UK)
October 1949
Binary
Electronic
Stored-program in Williams cathode ray tube memory and magnetic drum memory
Yes
CSIRAC (Australia)
November 1949
Binary
Electronic
Stored-program in mercury delay line memory
Yes
A succession of steadily more powerful and flexible computing devices were constructed in the 1930s and 1940s, gradually adding the key features that are seen in modern computers. The use of digital electronics (largely invented by Claude Shannon in 1937) and more flexible programmability were vitally important steps, but defining one point along this road as "the first digital electronic computer" is difficult (Shannon 1940). Notable achievements include:

EDSAC was one of the first computers to implement the stored program (von Neumann) architecture.
Konrad Zuse's electromechanical "Z machines". The Z3 (1941) was the first working machine featuring binary arithmetic, including floating point arithmetic and a measure of programmability. In 1998 the Z3 was proved to be Turing complete, therefore being the world's first operational computer.
The non-programmable Atanasoff–Berry Computer (1941) which used vacuum tube based computation, binary numbers, and regenerative capacitor memory.
The secret British Colossus computers (1943)[5], which had limited programmability but demonstrated that a device using thousands of tubes could be reasonably reliable and electronically reprogrammable. It was used for breaking German wartime codes.
The Harvard Mark I (1944), a large-scale electromechanical computer with limited programmability.
The U.S. Army's Ballistics Research Laboratory ENIAC (1946), which used decimal arithmetic and is sometimes called the first general purpose electronic computer (since Konrad Zuse's Z3 of 1941 used electromagnets instead of electronics). Initially, however, ENIAC had an inflexible architecture which essentially required rewiring to change its programming.
Several developers of ENIAC, recognizing its flaws, came up with a far more flexible and elegant design, which came to be known as the stored program architecture or von Neumann architecture. This design was first formally described by John von Neumann in the paper "First Draft of a Report on the EDVAC", published in 1945. A number of projects to develop computers based on the stored program architecture commenced around this time, the first of these being completed in Great Britain. The first to be demonstrated working was the Manchester Small-Scale Experimental Machine (SSEM) or "Baby". However, the EDSAC, completed a year after SSEM, was perhaps the first practical implementation of the stored program design. Shortly thereafter, the machine originally described by von Neumann's paper—EDVAC—was completed but did not see full-time use for an additional two years.
Nearly all modern computers implement some form of the stored program architecture, making it the single trait by which the word "computer" is now defined. By this standard, many earlier devices would no longer be called computers by today's definition, but are usually referred to as such in their historical context. While the technologies used in computers have changed dramatically since the first electronic, general-purpose computers of the 1940s, most still use the von Neumann architecture. The design made the universal computer a practical reality.

Microprocessors are miniaturized devices that often implement stored program CPUs.
Vacuum tube-based computers were in use throughout the 1950s. Vacuum tubes were largely replaced in the 1960s by transistor-based computers. When compared with tubes, transistors are smaller, faster, cheaper, use less power, and are more reliable. In the 1970s, integrated circuit technology and the subsequent creation of microprocessors, such as the Intel 4004, caused another generation of decreased size and cost, and another generation of increased speed and reliability. By the 1980s, computers became sufficiently small and cheap to replace simple mechanical controls in domestic appliances such as washing machines. The 1980s also witnessed home computers and the now ubiquitous personal computer. With the evolution of the Internet, personal computers are becoming as common as the television and the telephone in the household.

Stored program architecture
Main articles: Computer program and Computer programming
The defining feature of modern computers which distinguishes them from all other machines is that they can be programmed. That is to say that a list of instructions (the program) can be given to the computer and it will store them and carry them out at some time in the future.
In most cases, computer instructions are simple: add one number to another, move some data from one location to another, send a message to some external device, etc. These instructions are read from the computer's memory and are generally carried out (executed) in the order they were given. However, there are usually specialized instructions to tell the computer to jump ahead or backwards to some other place in the program and to carry on executing from there. These are called "jump" instructions (or branches). Furthermore, jump instructions may be made to happen conditionally so that different sequences of instructions may be used depending on the result of some previous calculation or some external event. Many computers directly support subroutines by providing a type of jump that "remembers" the location it jumped from and another instruction to return to the instruction following that jump instruction.
Program execution might be likened to reading a book. While a person will normally read each word and line in sequence, they may at times jump back to an earlier place in the text or skip sections that are not of interest. Similarly, a computer may sometimes go back and repeat the instructions in some section of the program over and over again until some internal condition is met. This is called the flow of control within the program and it is what allows the computer to perform tasks repeatedly without human intervention.
Comparatively, a person using a pocket calculator can perform a basic arithmetic operation such as adding two numbers with just a few button presses. But to add together all of the numbers from 1 to 1,000 would take thousands of button presses and a lot of time—with a near certainty of making a mistake. On the other hand, a computer may be programmed to do this with just a few simple instructions. For example: mov #0,sum ; set sum to 0
mov #1,num ; set num to 1
loop: add num,sum ; add num to sum
add #1,num ; add 1 to num
cmp num,#1000 ; compare num to 1000
ble loop ; if num <= 1000, go back to 'loop' halt ; end of program. stop running Once told to run this program, the computer will perform the repetitive addition task without further human intervention. It will almost never make a mistake and a modern PC can complete the task in about a millionth of a second.[6]
However, computers cannot "think" for themselves in the sense that they only solve problems in exactly the way they are programmed to. An intelligent human faced with the above addition task might soon realize that instead of actually adding up all the numbers one can simply use the equation

and arrive at the correct answer (500,500) with little work.[7] In other words, a computer programmed to add up the numbers one by one as in the example above would do exactly that without regard to efficiency or alternative solutions.

Programs

A 1970s punched card containing one line from a FORTRAN program. The card reads: "Z(1) = Y + W(1)" and is labelled "PROJ039" for identification purposes.
In practical terms, a computer program might include anywhere from a dozen instructions to many millions of instructions for something like a word processor or a web browser. A typical modern computer can execute billions of instructions every second and nearly never make a mistake over years of operation.
Large computer programs may take teams of computer programmers years to write and the probability of the entire program having been written completely in the manner intended is unlikely. Errors in computer programs are called bugs. Sometimes bugs are benign and do not affect the usefulness of the program, in other cases they might cause the program to completely fail (crash), in yet other cases there may be subtle problems. Sometimes otherwise benign bugs may be used for malicious intent, creating a security exploit. Bugs are usually not the fault of the computer. Since computers merely execute the instructions they are given, bugs are nearly always the result of programmer error or an oversight made in the program's design.[8]
In most computers, individual instructions are stored as machine code with each instruction being given a unique number (its operation code or opcode for short). The command to add two numbers together would have one opcode, the command to multiply them would have a different opcode and so on. The simplest computers are able to perform any of a handful of different instructions; the more complex computers have several hundred to choose from—each with a unique numerical code. Since the computer's memory is able to store numbers, it can also store the instruction codes. This leads to the important fact that entire programs (which are just lists of instructions) can be represented as lists of numbers and can themselves be manipulated inside the computer just as if they were numeric data. The fundamental concept of storing programs in the computer's memory alongside the data they operate on is the crux of the von Neumann, or stored program, architecture. In some cases, a computer might store some or all of its program in memory that is kept separate from the data it operates on. This is called the Harvard architecture after the Harvard Mark I computer. Modern von Neumann computers display some traits of the Harvard architecture in their designs, such as in CPU caches.
While it is possible to write computer programs as long lists of numbers (machine language) and this technique was used with many early computers,[9] it is extremely tedious to do so in practice, especially for complicated programs. Instead, each basic instruction can be given a short name that is indicative of its function and easy to remember—a mnemonic such as ADD, SUB, MULT or JUMP. These mnemonics are collectively known as a computer's assembly language. Converting programs written in assembly language into something the computer can actually understand (machine language) is usually done by a computer program called an assembler. Machine languages and the assembly languages that represent them (collectively termed low-level programming languages) tend to be unique to a particular type of computer. For instance, an ARM architecture computer (such as may be found in a PDA or a hand-held videogame) cannot understand the machine language of an Intel Pentium or the AMD Athlon 64 computer that might be in a PC.[10]
Though considerably easier than in machine language, writing long programs in assembly language is often difficult and error prone. Therefore, most complicated programs are written in more abstract high-level programming languages that are able to express the needs of the computer programmer more conveniently (and thereby help reduce programmer error). High level languages are usually "compiled" into machine language (or sometimes into assembly language and then into machine language) using another computer program called a compiler.[11] Since high level languages are more abstract than assembly language, it is possible to use different compilers to translate the same high level language program into the machine language of many different types of computer. This is part of the means by which software like video games may be made available for different computer architectures such as personal computers and various video game consoles.
The task of developing large software systems is an immense intellectual effort. Producing software with an acceptably high reliability on a predictable schedule and budget has proved historically to be a great challenge; the academic and professional discipline of software engineering concentrates specifically on this problem.

Example

A traffic light showing red.
Suppose a computer is being employed to drive a traffic light. A simple stored program might say:
Turn off all of the lights
Turn on the red light
Wait for sixty seconds
Turn off the red light
Turn on the green light
Wait for sixty seconds
Turn off the green light
Turn on the yellow light
Wait for two seconds
Turn off the yellow light
Jump to instruction number (2)
With this set of instructions, the computer would cycle the light continually through red, green, yellow and back to red again until told to stop running the program.
However, suppose there is a simple on/off switch connected to the computer that is intended to be used to make the light flash red while some maintenance operation is being performed. The program might then instruct the computer to:
Turn off all of the lights
Turn on the red light
Wait for sixty seconds
Turn off the red light
Turn on the green light
Wait for sixty seconds
Turn off the green light
Turn on the yellow light
Wait for two seconds
Turn off the yellow light
If the maintenance switch is NOT turned on then jump to instruction number 2
Turn on the red light
Wait for one second
Turn off the red light
Wait for one second
Jump to instruction number 11
In this manner, the computer is either running the instructions from number (2) to (11) over and over or its running the instructions from (11) down to (16) over and over, depending on the position of the switch.[12]

How computers work
Main articles: Central processing unit and Microprocessor
A general purpose computer has four main sections: the arithmetic and logic unit (ALU), the control unit, the memory, and the input and output devices (collectively termed I/O). These parts are interconnected by busses, often made of groups of wires.
The control unit, ALU, registers, and basic I/O (and often other hardware closely linked with these) are collectively known as a central processing unit (CPU). Early CPUs were composed of many separate components but since the mid-1970s CPUs have typically been constructed on a single integrated circuit called a microprocessor.

Control unit
Main articles: CPU design and Control unit
The control unit (often called a control system or central controller) directs the various components of a computer. It reads and interprets (decodes) instructions in the program one by one. The control system decodes each instruction and turns it into a series of control signals that operate the other parts of the computer.[13] Control systems in advanced computers may change the order of some instructions so as to improve performance.
A key component common to all CPUs is the program counter, a special memory cell (a register) that keeps track of which location in memory the next instruction is to be read from.[14]

Diagram showing how a particular MIPS architecture instruction would be decoded by the control system.
The control system's function is as follows—note that this is a simplified description, and some of these steps may be performed concurrently or in a different order depending on the type of CPU:
Read the code for the next instruction from the cell indicated by the program counter.
Decode the numerical code for the instruction into a set of commands or signals for each of the other systems.
Increment the program counter so it points to the next instruction.
Read whatever data the instruction requires from cells in memory (or perhaps from an input device). The location of this required data is typically stored within the instruction code.
Provide the necessary data to an ALU or register.
If the instruction requires an ALU or specialized hardware to complete, instruct the hardware to perform the requested operation.
Write the result from the ALU back to a memory location or to a register or perhaps an output device.
Jump back to step (1).
Since the program counter is (conceptually) just another set of memory cells, it can be changed by calculations done in the ALU. Adding 100 to the program counter would cause the next instruction to be read from a place 100 locations further down the program. Instructions that modify the program counter are often known as "jumps" and allow for loops (instructions that are repeated by the computer) and often conditional instruction execution (both examples of control flow).
It is noticeable that the sequence of operations that the control unit goes through to process an instruction is in itself like a short computer program - and indeed, in some more complex CPU designs, there is another yet smaller computer called a microsequencer that runs a microcode program that causes all of these events to happen.

Arithmetic/logic unit (ALU)
Main article: Arithmetic logic unit
The ALU is capable of performing two classes of operations: arithmetic and logic.
The set of arithmetic operations that a particular ALU supports may be limited to adding and subtracting or might include multiplying or dividing, trigonometry functions (sine, cosine, etc) and square roots. Some can only operate on whole numbers (integers) whilst others use floating point to represent real numbers—albeit with limited precision. However, any computer that is capable of performing just the simplest operations can be programmed to break down the more complex operations into simple steps that it can perform. Therefore, any computer can be programmed to perform any arithmetic operation—although it will take more time to do so if its ALU does not directly support the operation. An ALU may also compare numbers and return boolean truth values (true or false) depending on whether one is equal to, greater than or less than the other ("is 64 greater than 65?").
Logic operations involve Boolean logic: AND, OR, XOR and NOT. These can be useful both for creating complicated conditional statements and processing boolean logic.
Superscalar computers contain multiple ALUs so that they can process several instructions at the same time. Graphics processors and computers with SIMD and MIMD features often provide ALUs that can perform arithmetic on vectors and matrices.

Memory
Main article: Computer storage

Magnetic core memory was popular main memory for computers through the 1960s until it was completely replaced by semiconductor memory.
A computer's memory can be viewed as a list of cells into which numbers can be placed or read. Each cell has a numbered "address" and can store a single number. The computer can be instructed to "put the number 123 into the cell numbered 1357" or to "add the number that is in cell 1357 to the number that is in cell 2468 and put the answer into cell 1595". The information stored in memory may represent practically anything. Letters, numbers, even computer instructions can be placed into memory with equal ease. Since the CPU does not differentiate between different types of information, it is up to the software to give significance to what the memory sees as nothing but a series of numbers.
In almost all modern computers, each memory cell is set up to store binary numbers in groups of eight bits (called a byte). Each byte is able to represent 256 different numbers; either from 0 to 255 or -128 to +127. To store larger numbers, several consecutive bytes may be used (typically, two, four or eight). When negative numbers are required, they are usually stored in two's complement notation. Other arrangements are possible, but are usually not seen outside of specialized applications or historical contexts. A computer can store any kind of information in memory as long as it can be somehow represented in numerical form. Modern computers have billions or even trillions of bytes of memory.
The CPU contains a special set of memory cells called registers that can be read and written to much more rapidly than the main memory area. There are typically between two and one hundred registers depending on the type of CPU. Registers are used for the most frequently needed data items to avoid having to access main memory every time data is needed. Since data is constantly being worked on, reducing the need to access main memory (which is often slow compared to the ALU and control units) greatly increases the computer's speed.
Computer main memory comes in two principal varieties: random access memory or RAM and read-only memory or ROM. RAM can be read and written to anytime the CPU commands it, but ROM is pre-loaded with data and software that never changes, so the CPU can only read from it. ROM is typically used to store the computer's initial start-up instructions. In general, the contents of RAM is erased when the power to the computer is turned off while ROM retains its data indefinitely. In a PC, the ROM contains a specialized program called the BIOS that orchestrates loading the computer's operating system from the hard disk drive into RAM whenever the computer is turned on or reset. In embedded computers, which frequently do not have disk drives, all of the software required to perform the task may be stored in ROM. Software that is stored in ROM is often called firmware because it is notionally more like hardware than software. Flash memory blurs the distinction between ROM and RAM by retaining data when turned off but being rewritable like RAM. However, flash memory is typically much slower than conventional ROM and RAM so its use is restricted to applications where high speeds are not required.[15]
In more sophisticated computers there may be one or more RAM cache memories which are slower than registers but faster than main memory. Generally computers with this sort of cache are designed to move frequently needed data into the cache automatically, often without the need for any intervention on the programmer's part.

Input/output (I/O)
Main article: Input/output

Hard disks are common I/O devices used with computers.
I/O is the means by which a computer receives information from the outside world and sends results back. Devices that provide input or output to the computer are called peripherals. On a typical personal computer, peripherals include input devices like the keyboard and mouse, and output devices such as the display and printer. Hard disk drives, floppy disk drives and optical disc drives serve as both input and output devices. Computer networking is another form of I/O.
Often, I/O devices are complex computers in their own right with their own CPU and memory. A graphics processing unit might contain fifty or more tiny computers that perform the calculations necessary to display 3D graphics[citation needed]. Modern desktop computers contain many smaller computers that assist the main CPU in performing I/O.

Multitasking
Main article: Computer multitasking
While a computer may be viewed as running one gigantic program stored in its main memory, in some systems it is necessary to give the appearance of running several programs simultaneously. This is achieved by having the computer switch rapidly between running each program in turn. One means by which this is done is with a special signal called an interrupt which can periodically cause the computer to stop executing instructions where it was and do something else instead. By remembering where it was executing prior to the interrupt, the computer can return to that task later. If several programs are running "at the same time", then the interrupt generator might be causing several hundred interrupts per second, causing a program switch each time. Since modern computers typically execute instructions several orders of magnitude faster than human perception, it may appear that many programs are running at the same time even though only one is ever executing in any given instant. This method of multitasking is sometimes termed "time-sharing" since each program is allocated a "slice" of time in turn.
Before the era of cheap computers, the principle use for multitasking was to allow many people to share the same computer.
Seemingly, multitasking would cause a computer that is switching between several programs to run more slowly - in direct proportion to the number of programs it is running. However, most programs spend much of their time waiting for slow input/output devices to complete their tasks. If a program is waiting for the user to click on the mouse or press a key on the keyboard, then it will not take a "time slice" until the event it is waiting for has occurred. This frees up time for other programs to execute so that many programs may be run at the same time without unacceptable speed loss.

Multiprocessing
Main article: Multiprocessing

Cray designed many supercomputers that used multiprocessing heavily.
Some computers may divide their work between one or more separate CPUs, creating a multiprocessing configuration. Traditionally, this technique was utilized only in large and powerful computers such as supercomputers, mainframe computers and servers. However, multiprocessor and multi-core (multiple CPUs on a single integrated circuit) personal and laptop computers have become widely available and are beginning to see increased usage in lower-end markets as a result.
Supercomputers in particular often have highly unique architectures that differ significantly from the basic stored-program architecture and from general purpose computers.[16] They often feature thousands of CPUs, customized high-speed interconnects, and specialized computing hardware. Such designs tend to be useful only for specialized tasks due to the large scale of program organization required to successfully utilize most of the available resources at once. Supercomputers usually see usage in large-scale simulation, graphics rendering, and cryptography applications, as well as with other so-called "embarrassingly parallel" tasks.

Networking and the Internet
Main articles: Computer networking and Internet

Visualization of a portion of the routes on the Internet.
Computers have been used to coordinate information between multiple locations since the 1950s. The U.S. military's SAGE system was 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 United States began to link their computers together using telecommunications technology. This effort was funded by ARPA (now DARPA), 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. 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 almost ubiquitous. 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. "Wireless" networking, often utilizing mobile phone networks, has meant networking is becoming increasingly ubiquitous even in mobile computing environments.

Further topics

Hardware
Main article: Computer hardware
The term hardware covers all of those parts of a computer that are tangible objects. Circuits, displays, power supplies, cables, keyboards, printers and mice are all hardware.
History of computing hardware
First Generation (Mechanical/Electromechanical)
Calculators
Antikythera mechanism, Difference Engine, Norden bombsight
Programmable Devices
Jacquard loom, Analytical Engine, Harvard Mark I, Z3
Second Generation (Vacuum Tubes)
Calculators
Atanasoff–Berry Computer, IBM 604, UNIVAC 60, UNIVAC 120
Programmable Devices
Colossus, ENIAC, Manchester Small-Scale Experimental Machine, EDSAC, Manchester Mark I, CSIRAC, EDVAC, UNIVAC I, IBM 701, IBM 702, IBM 650, Z22
Third Generation (Discrete transistors and SSI, MSI, LSI Integrated circuits)
Mainframes
IBM 7090, IBM 7080, System/360, BUNCH
Minicomputer
PDP-8, PDP-11, System/32, System/36
Fourth Generation (VLSI integrated circuits)
Minicomputer
VAX, IBM System i
4-bit microcomputer
Intel 4004, Intel 4040
8-bit microcomputer
Intel 8008, Intel 8080, Motorola 6800, Motorola 6809, MOS Technology 6502, Zilog Z80
16-bit microcomputer
Intel 8088, Zilog Z8000, WDC 65816/65802
32-bit microcomputer
Intel 80386, Pentium, Motorola 68000, ARM architecture
64-bit microcomputer[17]
x86-64, PowerPC, MIPS, SPARC
Embedded computer
Intel 8048, Intel 8051
Personal computer
Desktop computer, Home computer, Laptop computer, Personal digital assistant (PDA), Portable computer, Tablet computer, Wearable computer
Theoretical/experimental
Quantum computer, Chemical computer, DNA computing, Optical computer, Spintronics based computer
Other Hardware Topics
Peripheral device (Input/output)
Input
Mouse, Keyboard, Joystick, Image scanner
Output
Monitor, Printer
Both
Floppy disk drive, Hard disk, Optical disc drive, Teleprinter
Computer busses
Short range
RS-232, SCSI, PCI, USB
Long range (Computer networking)
Ethernet, ATM, FDDI

Software
Main article: Computer software
Software refers to parts of the computer which do not have a material form, such as programs, data, protocols, etc. When software is stored in hardware that cannot easily be modified (such as BIOS ROM in an IBM PC compatible), it is sometimes called "firmware" to indicate that it falls into an uncertain area somewhere between hardware and software.
Computer software
Operating system
Unix/BSD
UNIX System V, AIX, HP-UX, Solaris (SunOS), IRIX, List of BSD operating systems
GNU/Linux
List of Linux distributions, Comparison of Linux distributions
Microsoft Windows
Windows 95, Windows 98, Windows NT, Windows 2000, Windows XP, Windows Vista, Windows CE
DOS
86-DOS (QDOS), PC-DOS, MS-DOS, FreeDOS
Mac OS
Mac OS classic, Mac OS X
Embedded and real-time
List of embedded operating systems
Experimental
Amoeba, Oberon/Bluebottle, Plan 9 from Bell Labs
Library
Multimedia
DirectX, OpenGL, OpenAL
Programming library
C standard library, Standard template library
Data
Protocol
TCP/IP, Kermit, FTP, HTTP, SMTP
File format
HTML, XML, JPEG, MPEG, PNG
User interface
Graphical user interface (WIMP)
Microsoft Windows, GNOME, KDE, QNX Photon, CDE, GEM
Text user interface
Command line interface, shells
Application
Office suite
Word processing, Desktop publishing, Presentation program, Database management system, Scheduling & Time management, Spreadsheet, Accounting software
Internet Access
Browser, E-mail client, Web server, Mail transfer agent, Instant messaging
Design and manufacturing
Computer-aided design, Computer-aided manufacturing, Plant management, Robotic manufacturing, Supply chain management
Graphics
Raster graphics editor, Vector graphics editor, 3D modeler, Animation editor, 3D computer graphics, Video editing, Image processing
Audio
Digital audio editor, Audio playback, Mixing, Audio synthesis, Computer music
Software Engineering
Compiler, Assembler, Interpreter, Debugger, Text Editor, Integrated development environment, Performance analysis, Revision control, Software configuration management
Educational
Edutainment, Educational game, Serious game, Flight simulator
Games
Strategy, Arcade, Puzzle, Simulation, First-person shooter, Platform, Massively multiplayer, Interactive fiction
Misc
Artificial intelligence, Antivirus software, Malware scanner, Installer/Package management systems, File manager

Programming languages
Programming languages provide various ways of specifying programs for computers to run. Unlike natural languages, programming languages are designed to permit no ambiguity and to be concise. They are purely written languages and are often difficult to read aloud. They are generally either translated into machine language by a compiler or an assembler before being run, or translated directly at run time by an interpreter. Sometimes programs are executed by a hybrid method of the two techniques. There are thousands of different programming languages—some intended to be general purpose, others useful only for highly specialized applications.
Programming Languages
Lists of programming languages
Timeline of programming languages, Categorical list of programming languages, Generational list of programming languages, Alphabetical list of programming languages, Non-English-based programming languages
Commonly used Assembly languages
ARM, MIPS, x86
Commonly used High level languages
BASIC, C, C++, C#, COBOL, Fortran, Java, Lisp, Pascal
Commonly used Scripting languages
Bourne script, JavaScript, Python, Ruby, PHP, Perl

Professions and organizations
As the use of computers has spread throughout society, there are an increasing number of careers involving computers. Following the theme of hardware, software and firmware, the brains of people who work in the industry are sometimes known irreverently as wetware or "meatware".
Computer-related professions
Hardware-related
Electrical engineering, Electronics engineering, Computer engineering, Telecommunications engineering, Optical engineering, Nanoscale engineering
Software-related
Computer science, Human-computer interaction, Information technology, Software engineering, Scientific computing, Web design, Desktop publishing
The need for computers to work well together and to be able to exchange information has spawned the need for many standards organizations, clubs and societies of both a formal and informal nature.
Organizations
Standards groups
ANSI, IEC, IEEE, IETF, ISO, W3C
Professional Societies
ACM, ACM Special Interest Groups, IET, IFIP
Free/Open source software groups
Free Software Foundation, Mozilla Foundation, Apache Software Foundation

See also

Look up Computer inWiktionary, the free dictionary.

Wikiquote has a collection of quotations related to:
Computers

Wikimedia Commons has media related to:
Computer
Computability theory
Computer science
Computing
Computers in fiction
Computer security and Computer insecurity
Electronic waste
List of computer term etymologies
Virtualization

Notes
^ In 1946, ENIAC consumed an estimated 174 kW. By comparison, a typical personal computer may use around 400 W; over four hundred times less. (Kempf 1961)
^ Early computers such as Colossus and ENIAC were able to process between 5 and 100 operations per second. A modern "commodity" microprocessor (as of 2007) can process billions of operations per second, and many of these operations are more complicated and useful than early computer operations.
^ Heron of Alexandria. Retrieved on 2008-01-15.
^ The Analytical Engine should not be confused with Babbage's difference engine which was a non-programmable mechanical calculator.
^ B. Jack Copeland, ed., Colossus: The Secrets of Bletchley Park's Codebreaking Computers, Oxford University Press, 2006
^ This program was written similarly to those for the PDP-11 minicomputer and shows some typical things a computer can do. All the text after the semicolons are comments for the benefit of human readers. These have no significance to the computer and are ignored. (Digital Equipment Corporation 1972)
^ Attempts are often made to create programs that can overcome this fundamental limitation of computers. Software that mimics learning and adaptation is part of artificial intelligence.
^ It is not universally true that bugs are solely due to programmer oversight. Computer hardware may fail or may itself have a fundamental problem that produces unexpected results in certain situations. For instance, the Pentium FDIV bug caused some Intel microprocessors in the early 1990s to produce inaccurate results for certain floating point division operations. This was caused by a flaw in the microprocessor design and resulted in a partial recall of the affected devices.
^ Even some later computers were commonly programmed directly in machine code. Some minicomputers like the DEC PDP-8 could be programmed directly from a panel of switches. However, this method was usually used only as part of the booting process. Most modern computers boot entirely automatically by reading a boot program from some non-volati memory.
^ However, there is sometimes some form of machine language compatibility between different computers. An x86-64compatible microprocessor like the AMD Athlon 64 is able to run most of the same programs that an Intel Core 2 microprocessor can, as well as programs designed for earlier microprocessors like the Intel Pentiums and Intel 80486. This contrasts with very early commercial computers, which were often one-of-a-kind and totally incompatible with other computers.
^ High level languages are also often interpretedrather than compiled. Interpreted languages are translated into machine code on the fly by another program called an interpreter.
^ Although this is a simple program, it contains a software bug. If the traffic signal is showing red when someone switches the "flash red" switch, it will cycle through green once more before starting to flash red as instructed. This bug is quite easy to fix by changing the program to repeatedly test the switch throughout each "wait" period—but writing large programs that have no bugs is exceedingly difficult.
^ The control unit's rule in interpreting instructions has varied somewhat in the past. While the control unit is solely responsible for instruction interpretation in most modern computers, this is not always the case. Many computers include some instructions that may only be partially interpreted by the control system and partially interpreted by another device. This is especially the case with specialized computing hardware that may be partially self-contained. For example, EDVAC, the first modern stored program computer to be designed, used a central control unit that only interpreted four instructions. All of the arithmetic-related instructions were passed on to its arithmetic unit and further decoded there.
^ Instructions often occupy more than one memory address, so the program counters usually increases by the number of memory locations required to store one instruction.
^ Flash memory also may only be rewritten a limited number of times before wearing out, making it less useful for heavy random access usage. (Verma 1988)
^ However, it is also very common to construct supercomputers out of many pieces of cheap commodity hardware; usually individual computers connected by networks. These so-called computer clusters can often provide supercomputer performance at a much lower cost than customized designs. While custom architectures are still used for most of the most powerful supercomputers, there has been a proliferation of cluster computers in recent years. ^ Most major 64-bit instruction set architectures are extensions of earlier designs. All of the architectures listed in this table existed in 32-bit forms before their 64-bit incarnations were introduced.

References
a Kempf, Karl (1961). "Historical Monograph: Electronic Computers Within the Ordnan Corps". Aberdeen Proving Ground (United States Army).
a Phillips, Tony (2000). The Antikythera Mechanism I. American Mathematical Society. Retrieved on 2006-04-05.
a Shannon, Claude Elwood (1940). "A symbolic analysis of relay and switching circuits". Massachusetts Institute of Technology.
a Digital Equipment Corporation (1972). PDP-11/40 Processor Handbook(PDF), Maynard, MA: Digital Equipment Corporation.
a Verma, G.; Mielke, N. (1988). "Reliability performance of ETOX based flash memories". IEEE International Reliability Physics Symposium.
a Meuer, Hans; Strohmaier, Erich; Simon, Horst; Stokes, Jon (2007). Inside the Machine: An Illustrated Introduction to Microprocessors and Computer Architecture. San Francisco: No Starch Press. ISBN 978-1-59327-104-6.