Supplementary Exams: Everything You Need to Know
One of the greatest goals of an average Pakistani teenager is to gain good marks in their final board exams. Parents in Pakistan place a lot of emphasis on studies and usually go to great lengths for their children to study well. Students are sent to tuition centers, cram schools, group studying sessions, and other similar places to study. This mindset causes students to also develop a dedication toward their academic performance. Despite the country's efforts to promote perfect academic performance, however, a lot of students still fail their annual board exams every year. But, Pakistan's education system gives these students another chance in the form of supplementary, or make-up, exams.
These exams offer students an opportunity for students to save their grades in matric or intermediate. Although a lot of students choose to reattempt their failed subject in the next annual exams along with the rest of their subjects, many students still opt for make-up exams.
Moreover, the students who take these exams aren't just those who failed in a subject or two. There are many students who got passing marks but were not satisfied with their percentile. Such students, sometimes, choose to take these exams to improve their percentile.
When are supplementary exams held in Pakistan?
Supplementary exams are held after the conclusion of annual board exams and the announcement of their results. Depending on the education board, they are held between September and November for all classes (9th, 10th, 11th, and 12th) in matric and intermediate. For example, the Board of Intermediate and Secondary Education (FBISE) conducts SSC Part I and II make-up exams in September every year, a month or two after the results are announced.
Supplementary exams are held after the conclusion of annual board exams and the announcement of their results. Depending on the education board, they are held between September and November for all classes (9th, 10th, 11th, and 12th) in matric and intermediate. For example, the Board of Intermediate and Secondary Education (FBISE) conducts SSC Part I and II make-up exams in September every year, a month or two after the results are announced.
Karachi Board of Secondary Education (BSEK), on the other hand, commences the make-up exams between October and November for SSC Part I and II, i.e. matric classes.
What are the eligibility criteria for supplementary exams in Pakistan?
According to FBISE, the eligibility criteria are as follows:
The candidate must have attempted SSC and/or HSSC (part I and II for both) Annual Examinations.
Only candidates who failed in less than two (02) subjects in their SSC/HSSC annual exams are permitted to attempt make-up exams.
All candidates who were issued Roll Numbers and admit cards for Annual Examinations (SSC, HSSC) but could not appear in any exams, i.e. were absent in all papers.
Candidates who wish to improve their marks/grades are also eligible to attempt make-up exams.
Candidates who failed in more than two (02) subjects will have to appear in all subjects of their examination, such as SSC-I or HSSC-II, in the next Annual Examinations as fresh candidates.
Candidates who failed in less than two (02) subjects will be placed under compartment and will be permitted to appear only in their failed subjects/papers in the examinations. Such candidates will have three chances for subsequent attempts: supplementary exams, annual exams, and next year's supplementary exams.
This was everything that you needed to know about make-up exams in the education system of Pakistan for matric and intermediate. If you're a university student, your guidelines will depend on your university.
Don't be worried about how you will prepare for your supplementary exams. Instead, convert that worry into determination and focus on strengthening all your weak points. Make sure that you will no longer repeat the mistakes you made that caused you to fail or get bad marks.
Supplementary exams are a blessing for students who failed in SSC/HSSC. Here's everything you need to know about these Visit. https://tutoria.pk/
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Science
Science[nb 1] is a systematic enterprise that builds and organizes knowledge in the form of testable explanations and predictions about the universe
- 1 Natural science
- 2 Social sciences
- 3 Formal sciences
- 4 Applied sciences
- 5 See also
- 6 Notes
- 7 References
- 8 External links
History of science
- 1 Early cultures
- 2 Science in the Middle Ages
- 3 Impact of science in Europe
- 4 Modern science
- 5 Academic study
- 6 See also
- 7 Notes and references
- 8 Further reading
- 9 External links
Periodic table
- 1 Overview
- 2 Grouping methods
- 3 Periodic trends
- 4 History
- 5 Alternative structures
- 6 Open questions and controversies
- 7 See also
- 8 Notes
- 9 References
- 10 Bibliography
- 11 External links
Ten most commonelements in the Milky Way Galaxy estimated spectroscopically[45]
Z Element Mass fraction in parts per million 1 Hydrogen 739,000 71 × mass of oxygen (red bar) 2 Helium 240,000 23 × mass of oxygen (red bar) 8 Oxygen 10,400 6 Carbon 4,600 10 Neon 1,340 26 Iron 1,090 7 Nitrogen 960 14 Silicon 650 12 Magnesium 580 16 Sulfur 440
Diamond is the hardest known natural material (third-hardest known material after aggregated diamond nanorods and ultrahard fullerite), and is an allotrope of carbon. A diamond is a transparent crystal of tetrahedrally bonded carbon atoms. Diamonds have been adapted for many uses because of the material's exceptional physical characteristics. Most notable are its extreme hardness of diamond, its high dispersion index, and high thermal conductivity.
Fields of Chemistry (books)
- Analytical chemistry: Chromatography, Spectroscopy
- Biochemistry: Molecular biology
- Crystal Chemistry
- Environmental chemistry: Geochemistry
- Inorganic chemistry: Inorganic reactions
- Materials science: Nanotechnology, Glass, Ceramics
- Medicinal chemistry
- Nuclear chemistry
- Organic chemistry: Functional groups, Organic compounds, Organic reactions
- Organometallic chemistry
- Pharmacy
- Physical chemistry: Electrochemistry, Quantum chemistry
- Polymer chemistry
- Supramolecular chemistry
- Theoretical chemistry: Computational chemistry
Computer
A computer is a general purpose device that can be programmed to carry out a set of arithmetic or logical operations automatically. Since a sequence of operations can be readily changed, the computer can solve more than one kind of problem.
Conventionally, a computer consists of at least one processing element, typically a central processing unit (CPU), and some form of memory. The processing element carries out arithmetic and logic operations, and a sequencing and control unit can change the order of operations in response to stored information. Peripheral devices allow information to be retrieved from an external source, and the result of operations saved and retrieved.
Contents
- 1 Etymology
- 2 History
- 3 Programs
- 4 Components
- 5 Networking and the Internet
- 6 Misconceptions
- 7 Future
- 8 Further topics
- 9 Hardware
- 10 Software
- 11 Languages
- 12 Types of computers
- 13 Input Devices
- 14 Output Devices
- 15 Professions and organizations
- 16 See also
- 17 Notes
- 18 References
- 19 External links
Etymology
The first known use of the word "computer" was in 1613 in a book called The Yong Mans Gleanings by English writer Richard Braithwait: "I haue read the truest computer of Times, and the best Arithmetician that euer breathed, and he reduceth thy dayes into a short number." It referred to a person who carried out calculations, or computations. The word continued with the same meaning until the middle of the 20th century. From the end of the 19th century the word began to take on its more familiar meaning, a machine that carries out computations.[1]
History
Main article: History of computing hardwarePre-twentieth century
Many mechanical aids to calculation and measurement were constructed for astronomical and navigation use. The planisphere was a star chart invented by Abū Rayhān al-Bīrūnī in the early 11th century.[5] The astrolabe was invented in the Hellenistic world in either the 1st or 2nd centuries BC and is often attributed to Hipparchus. A combination of the planisphere and dioptra, the astrolabe was effectively an analog computer capable of working out several different kinds of problems in spherical astronomy. An astrolabe incorporating a mechanical calendar computer[6][7] and gear-wheels was invented by Abi Bakr of Isfahan, Persia in 1235.[8] Abū Rayhān al-Bīrūnī invented the first mechanical geared lunisolar calendar astrolabe,[9] an early fixed-wired knowledge processing machine[10] with a gear train and gear-wheels,[11] circa 1000 AD.
The sector, a calculating instrument used for solving problems in proportion, trigonometry, multiplication and division, and for various functions, such as squares and cube roots, was developed in the late 16th century and found application in gunnery, surveying and navigation.
The planimeter was a manual instrument to calculate the area of a closed figure by tracing over it with a mechanical linkage.
In the 1770s Pierre Jaquet-Droz, a Swiss watchmaker, built a mechanical doll (automata) that could write holding a quill pen. By switching the number and order of its internal wheels different letters, and hence different messages, could be produced. In effect, it could be mechanically "programmed" to read instructions. Along with two other complex machines, the doll is at the Musée d'Art et d'Histoire of Neuchâtel, Switzerland, and still operates.[12]
The tide-predicting machine invented by Sir William Thomson in 1872 was of great utility to navigation in shallow waters. It used a system of pulleys and wires to automatically calculate predicted tide levels for a set period at a particular location.
The differential analyser, a mechanical analog computer designed to solve differential equations by integration, used wheel-and-disc mechanisms to perform the integration. In 1876 Lord Kelvin had already discussed the possible construction of such calculators, but he had been stymied by the limited output torque of the ball-and-disk integrators.[13] In a differential analyzer, the output of one integrator drove the input of the next integrator, or a graphing output. The torque amplifier was the advance that allowed these machines to work. Starting in the 1920s, Vannevar Bush and others developed mechanical differential analyzers.
First computing device
The machine was about a century ahead of its time. All the parts for his machine had to be made by hand — this was a major problem for a device with thousands of parts. Eventually, the project was dissolved with the decision of the British Government to cease funding. Babbage's failure to complete the analytical engine can be chiefly attributed to difficulties not only of politics and financing, but also to his desire to develop an increasingly sophisticated computer and to move ahead faster than anyone else could follow. Nevertheless, his son, Henry Babbage, completed a simplified version of the analytical engine's computing unit (the mill) in 1888. He gave a successful demonstration of its use in computing tables in 1906.
Analog computers
The first modern analog computer was a tide-predicting machine, invented by Sir William Thomson in 1872. The differential analyser, a mechanical analog computer designed to solve differential equations by integration using wheel-and-disc mechanisms, was conceptualized in 1876 by James Thomson, the brother of the more famous Lord Kelvin.[13]
The art of mechanical analog computing reached its zenith with the differential analyzer, built by H. L. Hazen and Vannevar Bush at MIT starting in 1927. This built on the mechanical integrators of James Thomson and the torque amplifiers invented by H. W. Nieman. A dozen of these devices were built before their obsolescence became obvious.
By the 1950s the success of digital electronic computers had spelled the end for most analog computing machines, but analog computers remain in use in some specialized applications such as education (control systems) and aircraft (slide rule).
Digital Computers
Electromechanical
By 1938 the United States Navy had developed an electromechanical analog computer small enough to use aboard a submarine. This was the Torpedo Data Computer, which used trigonometry to solve the problem of firing a torpedo at a moving target. During World War II similar devices were developed in other countries as well.
In 1941, Zuse followed his earlier machine up with the Z3, the world's first working electromechanical programmable, fully automatic digital computer.[19][20] The Z3 was built with 2000 relays, implementing a 22 bit word length that operated at a clock frequency of about 5–10 Hz.[21] Program code was supplied on punched film while data could be stored in 64 words of memory or supplied from the keyboard. It was quite similar to modern machines in some respects, pioneering numerous advances such as floating point numbers. Replacement of the hard-to-implement decimal system (used in Charles Babbage's earlier design) by the simpler binary system meant that Zuse's machines were easier to build and potentially more reliable, given the technologies available at that time.[22] The Z3 was Turing complete.[23][24]
Vacuum tubes and digital electronic circuits
Purely electronic circuit elements soon replaced their mechanical and electromechanical equivalents, at the same time that digital calculation replaced analog. The engineer Tommy Flowers, working at the Post Office Research Station in London in the 1930s, began to explore the possible use of electronics for the telephone exchange. Experimental equipment that he built in 1934 went into operation 5 years later, converting a portion of the telephone exchange network into an electronic data processing system, using thousands of vacuum tubes.[17] In the US, John Vincent Atanasoff and Clifford E. Berry of Iowa State University developed and tested the Atanasoff–Berry Computer (ABC) in 1942,[25] the first "automatic electronic digital computer".[26] This design was also all-electronic and used about 300 vacuum tubes, with capacitors fixed in a mechanically rotating drum for memory.[27]
Colossus was the world's first electronic digital programmable computer.[17] It used a large number of valves (vacuum tubes). It had paper-tape input and was capable of being configured to perform a variety of boolean logical operations on its data, but it was not Turing-complete. Nine Mk II Colossi were built (The Mk I was converted to a Mk II making ten machines in total). Colossus Mark I contained 1500 thermionic valves (tubes), but Mark II with 2400 valves, was both 5 times faster and simpler to operate than Mark 1, greatly speeding the decoding process.[30][31]
It combined the high speed of electronics with the ability to be programmed for many complex problems. It could add or subtract 5000 times a second, a thousand times faster than any other machine. It also had modules to multiply, divide, and square root. High speed memory was limited to 20 words (about 80 bytes). Built under the direction of John Mauchly and J. Presper Eckert at the University of Pennsylvania, ENIAC's development and construction lasted from 1943 to full operation at the end of 1945. The machine was huge, weighing 30 tons, using 200 kilowatts of electric power and contained over 18,000 vacuum tubes, 1,500 relays, and hundreds of thousands of resistors, capacitors, and inductors.[33]
Modern computers
The concept of modern computer
The principle of the modern computer was proposed by Alan Turing, in his seminal 1936 paper,[34] On Computable Numbers. Turing proposed a simple device that he called "Universal Computing machine" that is later known as a Universal Turing machine. He proved that such machine is capable of computing anything that is computable by executing instructions (program) stored on tape, allowing the machine to be programmable.
The fundamental concept of Turing's design is stored program, where all instruction for computing is stored in the memory.
Von Neumann acknowledged that the central concept of the modern computer was due to this paper.[35] Turing machines are to this day a central object of study in theory of computation. Except for the limitations imposed by their finite memory stores, modern computers are said to be Turing-complete, which is to say, they have algorithm execution capability equivalent to a universal Turing machine.
Stored programs
The Mark 1 in turn quickly became the prototype for the Ferranti Mark 1, the world's first commercially available general-purpose computer.[39] Built by Ferranti, it was delivered to the University of Manchester in February 1951. At least seven of these later machines were delivered between 1953 and 1957, one of them to Shell labs in Amsterdam.[40] In October 1947, the directors of British catering company J. Lyons & Company decided to take an active role in promoting the commercial development of computers. The LEO I computer became operational in April 1951[41] and ran the world's first regular routine office computer job.
Transistors
At the University of Manchester, a team under the leadership of Tom Kilburn designed and built a machine using the newly developed transistors instead of valves.[42] Their first transistorised computer and the first in the world, was operational by 1953, and a second version was completed there in April 1955. However, the machine did make use of valves to generate its 125 kHz clock waveforms and in the circuitry to read and write on its magnetic drum memory, so it was not the first completely transistorized computer. That distinction goes to the Harwell CADET of 1955,[43] built by the electronics division of the Atomic Energy Research Establishment at Harwell.[44][43]
Integrated circuits
The next great advance in computing power came with the advent of the integrated circuit. The idea of the integrated circuit was first conceived by a radar scientist working for the Royal Radar Establishment of the Ministry of Defence, Geoffrey W.A. Dummer. Dummer presented the first public description of an integrated circuit at the Symposium on Progress in Quality Electronic Components in Washington, D.C. on 7 May 1952.[45]
The first practical ICs were invented by Jack Kilby at Texas Instruments and Robert Noyce at Fairchild Semiconductor.[46] Kilby recorded his initial ideas concerning the integrated circuit in July 1958, successfully demonstrating the first working integrated example on 12 September 1958.[47] In his patent application of 6 February 1959, Kilby described his new device as "a body of semiconductor material ... wherein all the components of the electronic circuit are completely integrated".[48][49] Noyce also came up with his own idea of an integrated circuit half a year later than Kilby.[50] His chip solved many practical problems that Kilby's had not. Produced at Fairchild Semiconductor, it was made of silicon, whereas Kilby's chip was made of germanium.
This new development heralded an explosion in the commercial and personal use of computers and led to the invention of the microprocessor. While the subject of exactly which device was the first microprocessor is contentious, partly due to lack of agreement on the exact definition of the term "microprocessor", it is largely undisputed that the first single-chip microprocessor was the Intel 4004,[51] designed and realized by Ted Hoff, Federico Faggin, and Stanley Mazor at Intel.[52]
Mobile computers become dominant
With the continued miniaturization of computing resources, and advancements in portable battery life, portable computers grew in popularity in the 2000s.[53] The same developments that spurred the growth of laptop computers and other portable computers allowed manufacturers to integrate computing resources into cellular phones. These so-called smartphones and tablets run on a variety of operating systems and have become the dominant computing device on the market, with manufacturers reporting having shipped an estimated 237 million devices in 2Q 2013.[54]
Programs
The defining feature of modern computers which distinguishes them from all other machines is that they can be programmed. That is to say that some type of instructions (the program) can be given to the computer, and it will process them. Modern computers based on the von Neumann architecture often have machine code in the form of an imperative programming language.
In practical terms, a computer program may be just a few instructions or extend to many millions of instructions, as do the programs for word processors and web browsers for example. A typical modern computer can execute billions of instructions per second (gigaflops) and rarely makes a mistake over many years of operation. Large computer programs consisting of several million instructions may take teams of programmers years to write, and due to the complexity of the task almost certainly contain errors.
Stored program architecture
Main articles: Computer program and Computer programming
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. The following example is written in the MIPS assembly language:
begin: addi $8, $0, 0 # initialize sum to 0 addi $9, $0, 1 # set first number to add = 1 loop: slti $10, $9, 1000 # check if the number is less than 1000 beq $10, $0, finish # if odd number is greater than n then exit add $8, $8, $9 # update sum addi $9, $9, 1 # get next number j loop # repeat the summing process finish: add $2, $8, $0 # put sum in output register
Machine code
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 these instructions) can be represented as lists of numbers and can themselves be manipulated inside the computer in the same way as 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[citation needed], 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 while this technique was used with many early computers,[55] it is extremely tedious and potentially error-prone 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.
Programming language
Main article: Programming languageProgramming 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 code 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.
Low-level languages
Main article: Low-level programming languageMachine 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.[56]
High-level languages/Third Generation Language
Main article: High-level programming languageThough considerably easier than in machine language, writing long programs in assembly language is often difficult and is also error prone. Therefore, most practical programs are written in more abstract high-level programming languages that are able to express the needs of the 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.[57] High level languages are less related to the workings of the target computer than assembly language, and more related to the language and structure of the problem(s) to be solved by the final program. It is therefore often 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.
Fourth Generation Languages
These 4G languages are less procedural than 3G languages. The benefit of 4GL is that it provides ways to obtain information without requiring the direct help of a programmer. Example of 4GL is SQL.
Program design
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Bugs
Main article: Software bug
Admiral Grace Hopper, an American computer scientist and developer of the first compiler, is credited for having first used the term "bugs" in computing after a dead moth was found shorting a relay in the Harvard Mark II computer in September 1947.[59]
Components
Main articles: Central processing unit and Microprocessor
Inside each of these parts are thousands to trillions of small electrical circuits which can be turned off or on by means of an electronic switch. Each circuit represents a bit (binary digit) of information so that when the circuit is on it represents a "1", and when off it represents a "0" (in positive logic representation). The circuits are arranged in logic gates so that one or more of the circuits may control the state of one or more of the other circuits.
Control unit
Main articles: CPU design and Control unit
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.[61]
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).
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, which runs a microcode program that causes all of these events to happen.
Central processing unit (CPU)
The control unit, ALU, and registers 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.
Arithmetic logic unit (ALU)
Main article: Arithmetic logic unitThe ALU is capable of performing two classes of operations: arithmetic and logic.[62]
The set of arithmetic operations that a particular ALU supports may be limited to addition and subtraction, or might include multiplication, division, trigonometry functions such as 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 for creating complicated conditional statements and processing boolean logic.
Superscalar computers may contain multiple ALUs, allowing them to process several instructions simultaneously.[63] Graphics processors and computers with SIMD and MIMD features often contain ALUs that can perform arithmetic on vectors and matrices.
Memory
Main article: Computer data storage
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 (28 = 256); 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 if it can be represented numerically. 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. As 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
- read-only memory or ROM
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
I/O devices are often 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 multitaskingWhile 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 multitasking i.e. having the computer switch rapidly between running each program in turn.[67]
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.[68]
Before the era of cheap computers, the principal 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, but 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 simultaneously without unacceptable speed loss.
Multiprocessing
Main article: Multiprocessing
Supercomputers in particular often have highly unique architectures that differ significantly from the basic stored-program architecture and from general purpose computers.[69] 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
In the 1970s, computer engineers at research institutions throughout the United States began to link their computers together using telecommunications technology. The effort was funded by ARPA (now DARPA), and the computer network that resulted was called the ARPANET.[71] 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.
Computer architecture paradigms
There are many types of computer architectures:
- Quantum computer vs. Chemical computer
- Scalar processor vs. Vector processor
- Non-Uniform Memory Access (NUMA) computers
- Register machine vs. Stack machine
- Harvard architecture vs. von Neumann architecture
- Cellular architecture
Logic gates are a common abstraction which can apply to most of the above digital or analog paradigms.
The ability to store and execute lists of instructions called programs makes computers extremely versatile, distinguishing them from calculators. The Church–Turing thesis is a mathematical statement of this versatility: any computer with a minimum capability (being Turing-complete) is, in principle, capable of performing the same tasks that any other computer can perform. Therefore, any type of computer (netbook, supercomputer, cellular automaton, etc.) is able to perform the same computational tasks, given enough time and storage capacity.
Misconceptions
Main articles: Human computer and Harvard Computers
Unconventional computing
Main article: Unconventional computingHistorically, computers evolved from mechanical computers and eventually from vacuum tubes to transistors. However, conceptually computational systems as flexible as a personal computer can be built out of almost anything. For example, a computer can be made out of billiard balls (billiard ball computer); an often quoted example.[citation needed] More realistically, modern computers are made out of transistors made of photolithographed semiconductors.
Future
There is active research to make computers out of many promising new types of technology, such as optical computers, DNA computers, neural computers, and quantum computers. Most computers are universal, and are able to calculate any computable function, and are limited only by their memory capacity and operating speed. However different designs of computers can give very different performance for particular problems; for example quantum computers can potentially break some modern encryption algorithms (by quantum factoring) very quickly.
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