The Components of Computer

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Computer:

The machine which assists in processing raw data and display the data after assessing and evaluating them as per asking of the users along with the facility to store the information, is called a “Computer”.

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Figure: A computer[1]

 

The Components of a Computer:

According to the ehow website page

general purpose computer has the following four components:

  1. Input ,
  2. Output,
  3. Storage Unit/ Memory,
  4. Central Processing Unit

 

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Figure: the Components of Computer

  1. Input Unit:

The devices which provide the facility to users to interact with the machine and give command to perform a certain tasks are called Input device. The list of various input devices used for computer as per their purpose are as follows:

  1. Keyboard,
  2. Image Scanner,
  3. Microphone,
  4. Pointing Device( Graphics tablet, joystick, light pen, mouse(optical), pointing stick)
  5. Touchpad,
  6. Touch screen,
  7. Trackball,
  8. Webcam(soft cam),
  9. Refreshable Braille display

 

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Figure: The input devices of Computer

 

 

  1. Keyboard:

In computing, a keyboard is a typewriter-style device, which uses an arrangement of buttons or keys, to act as mechanical levers or electronic switches. Following the decline of punch cards and paper tape, interaction via teleprinter-style keyboards became the main input device for computers.

A keyboard typically has characters engraved or printed on the keys and each press of a key typically corresponds to a single written symbol. However, to produce some symbols requires pressing and holding several keys simultaneously or in sequence. While most keyboard keys produce letters, numbers or signs (characters), other keys or simultaneous key presses can produce actions or execute computer commands.

In normal usage, the keyboard is used to type text and numbers into a word processor, text editor or other programs. In a modern computer, the interpretation of key presses is generally left to the software. A computer keyboard distinguishes each physical key from every other and reports all key presses to the controlling software. Keyboards are also used for computer gaming, either with regular keyboards or by using keyboards with special gaming features, which can expedite frequently used keystroke combinations. A keyboard is also used to give commands to the operating system of a computer, such as Windows’ Control-Alt-Delete combination, which brings up a task window or shuts down the machine. A command-line interface is a type of user interface operated entirely through a keyboard, or another device doing the job of one.

  1. Image Scanner:

In computing, an image scanner—often abbreviated to just scanner, although the term is ambiguous out of context (barcode scanner, CAT scanner, etc.)—is a device that optically scans images, printed text, handwriting, or an object, and converts it to a digital image. Commonly used in offices are variations of the desktop flatbed scanner where the document is placed on a glass window for scanning. Hand-held scanners, where the device is moved by hand, have evolved from text scanning “wands” to 3D scanners used for industrial design, reverse engineering, test and measurement, orthotics, gaming and other applications. Mechanically driven scanners that move the document are typically used for large-format documents, where a flatbed design would be impractical.

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Figure: An Image Scanner

 

 

  1. Microphone:

A microphone (colloquially called a mic or mike; both pronounced /ˈmaɪk/) is an acoustic-to-electric transducer or sensor that converts sound in air into an electrical signal. Microphones are used in many applications such as telephones, tape recorders, karaoke systems, hearing aids, motion picture production, live and recorded audio engineering, FRS radios, megaphones, in radio and television broadcasting and in computers for recording voice, speech recognition, VoIP, and for non-acoustic purposes such as ultrasonic checking or knock sensors.

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Figure: a microphone

 

  1. Pointing Device:

A pointing device is an input interface (specifically a human interface device) that allows a user to input spatial (i.e., continuous and multidimensional) data to a computer. CAD systems and graphical user interfaces (GUI) allow the user to control and provide data to the computer using physical gestures — point, click, and drag — for example, by moving a hand-held mouse across the surface of the physical desktop and activating switches on the mouse. Movements of the pointing device are echoed on the screen by movements of the pointer (or cursor) and other visual changes.

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Figure: mouse (an example optical pointing device)

 

  1. Touchpad:

A touchpad /ˈtʌtʃpæd/ or trackpad /ˈtrækpæd/ is a pointing device featuring a tactile sensor, a specialized surface that can translate the motion and position of a user’s fingers to a relative position on the operating system that is outputted to the screen. Touchpads are a common feature of laptop computers, and are also used as a substitute for a mouse where desk space is scarce. Because they vary in size, they can also be found on personal digital assistants (PDAs) and some portable media players. Wireless touch pads such as Apple’s Magic Trackpad are also available as detached accessories.

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Figure: parts of touchpad and the direction of using it.

  1. Refreshable Braille display

A refreshable braille display or braille terminal is an electro-mechanical device for displaying braille characters, usually by means of round-tipped pins raised through holes in a flat surface. Blind computer users, who cannot use a computer monitor, use it to read text output. Speech synthesizers are also commonly used for the same task, and a blind user may switch between the two systems or use both at the same time depending on circumstances.

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Figure : a refreshable Braille Display

  1. Output Device:

Output devices are those devices which facilitates the users to get the results of actions or commands in the suitable form of sensory receiver’s of users body such as visible, audible or touchable form etc. .

The output devices used as part of Computer are:

  1. Monitor,
  2. Refreshable braille display,
  3. Printer,
  4. Speaker,
  5. Plotter

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Figure: A typical optical mouse

  1. Storage Unit:

The unit of the computer which assists users in keeping the data and information safe and in retrieving the information as per the user’s commands, is called Storage Unit or Memory Unit.

The Types of Storage Units:

The types of memory used in the computer systems are as follows:

  1. Volatile Memory,
  2. Non-volatile Memory

 

3.1.      Volatile Memory:

Volatile memory is computer memory that requires power to maintain the stored information. Most modern semiconductor volatile memory is either Static RAM or dynamic RAM. SRAM retains its contents as long as the power is connected and is easy to interface to but uses six transistors per bit. Dynamic RAM is more complicated to interface to and control and needs regular refresh cycles to prevent its contents being lost. However, DRAM uses only one transistor and a capacitor per bit, allowing it to reach much higher densities and, with more bits on a memory chip, be much cheaper per bit. SRAM is not worthwhile for desktop system memory, where DRAM dominates, but is used for their cache memories. SRAM is commonplace in small embedded systems, which might only need tens of kilobytes or less. Forthcoming volatile memory technologies that hope to replace or compete with SRAM and DRAM include Z-RAM, TTRAM, A-RAM and ETA RAM.

 

3.2.      Non-volatile Memory:

Non-volatile memory is computer memory that can retain the stored information even when not powered. Examples of non-volatile memory include read-only memory, flash memory, most types of magnetic computer storage devices (e.g. hard disks, floppy discs and magnetic tape), optical discs, and early computer storage methods such as paper tape and punched cards. Forthcoming non-volatile memory technologies include FeRAM, CBRAM, PRAM, SONOS, RRAM, Racetrack memory, NRAM and Millipede.

According to Buzzle.com ,

Computer memory are of mainly two types-

  1. Primary memory,
  2. Secondary Memory.

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Figure: The Types of Computer Memory

PRIMARY MEMORY

Primary Memory (also called main memory), is used for immediate access of data by the processor. While primary memory storage demonstrates faster processing ability, it is costly and hence is not largely used for data storage. Most computer systems around the world use primary memory only for bootstrapping and related purposes, and use secondary memory devices for personal data storage purpose.

Primary Memory can be divided into two types – Random Access Memory (RAM) and Read Only Memory (ROM).

RAM retains its contents as long as the power supply is on. A RAM chip is used as primary memory in most computers today. However, older computers (in the ’80s) used ROM devices (floppy disks, magnetic tapes, paper clips or punches; but more prominently floppy disks) as primary memory mechanism.

Random Access Memory (RAM)

RAM is a memory scheme within the computer system responsible for storing data on a temporary basis, so that it can be promptly accessed by the processor as and when needed. It is volatile in nature, which means that data will be erased once supply to the storage device is turned off. RAM stores data randomly and the processor accesses these data randomly from the RAM storage. The information stored in the RAM is typically loaded from the computer’s hard disk, and includes data related to the operating system and certain applications. When the system is switched off, the RAM loses all stored information. The data remains stored on secondary storage though, and can be retained when the system is running again. .

There are primarily two forms of RAM: Static RAM (SRAM) and Dynamic RAM (DRAM).

Static RAM: The most expensive of the lot, SRAM uses bistable latching circuitry to store one bit each, and hence is faster than its counterpart. Its high price prevents it from being widely used in everyday computing machines, but many modern machines use SRAM as the processor’s cache register.

Dynamic RAM: Widely used in modern computers as primary memory, DRAM is slower than SRAM, but is inexpensive due to its one transistor-one capacitor paired assembly of memory storage.

Read Only Memory (ROM)

Unlike RAM, ROM is a permanent form of storage. ROM stays active regardless of whether power supply to it is turned on or off. In spite of this, ROM was used (in rare cases is still used) as the primary device for most computers back in the ’80s. This was because ROM devices do not allow data stored on them to be modified. As the name itself suggests, data can only be accessed and read by the user, not overwritten, upgraded, or modified. This made it an ideal choice as bootable devices for old computers, programmable interpreters, and portable OS files carrier. The system programs stored on a ROM device could never be altered and hence, stayed secure for use.

The ROM memory used in modern computers is pre-programmed by the circuit manufacturer and cannot be altered by the user. The main reason why ROMs are not widely used in modern computer systems is because of the masking and error-retrieval costs. These processes are very expensive, and virtually negate the inexpensive manufacturing involved.

SECONDARY MEMORY

Secondary memory is available on mass storage devices for permanent data storage. Data stored on a secondary device is retained even when it is not supplied any power. This data can be transported in most cases, and looks and appears the same on any machine, irrespective of where the data was first copied onto the secondary storage device.

Unlike primary memory, secondary memory is not directly accessible by the computer. When a computer needs to run or execute an application stored in secondary memory, it first brings it to primary memory storage for a while, to control and carry out its execution. Once execution of the application is done, the processor releases the application and restores its control and memory data with the secondary memory device.

Popular secondary memory devices include hard disk drives, flash drives (pen drives, memory cards etc.), and zip drives. A couple of decades ago, as the ‘personal computer’ (PC) revolution was gathering storm, especially in America, floppy disks had acquired almost a cult status amongst PC users. Eventually, floppy disks were phased out by a better technology – a contemporary form of the optical drive called the Compact Disc or CD. CDs came with better speed and larger storage alternatives as compared to floppies. DVDs eventually took over the mantle from CDs, courtesy their ability to store almost 4 times more data. Although DVDs are still widely used, the preferred devices of secondary storage nowadays are portable hard disk drives or flash drives.

Punch Devices

The essential data storage techniques of the ’50s and ’60s, punch tapes and punch cards have become passé since the advent of newer data storage formats.

Punch Tapes:

A 0.1 mm thick paper strip was used to store data in the form of punched holes. A keyboard was used to punch the desired alphabet onto the tape. This alphabet was represented on the tape by a certain number and a select pattern of holes. A separate tape machine was used to send and receive these tapes for distance communication purposes. For computing purposes, stored data on the tapes would be read by the processing unit’s inbuilt decoding machine.

Punch Cards:

Primarily used in textile and handloom industries, punch cards stored instructions of operation for machines. Early digital computers made punch cards popular as data storage assemblies. Their working is pretty much similar to that of punch tapes, except for the fact that instead of paper strips, this technique uses cards about 3¼ inches × 7⅜ inches in size. Around the 1920s and 1930s, IBM hit upon a series of card innovations which enabled pre-punched data verification cards and cards with the ability to read alphabets, numbers, and signs (symbols) on a single multipurpose card.
Magnetic Tape
Magnetic tape as a recording technique was invented in 1928. This formed the basis for magnetic digital information storage. This form of data storage gained immense popularity in the ’70s, when magnetic tapes were wound around 10.6-inch reels. The device used for the read-write operations on these tapes is called a tape drive. Until the early 1980s, magnetic tape drives were huge external devices. With the introduction of IBM’s 3480 family of magnetic tape cartridges, most magnetic tape storage assembly went inside the central processing unit.

Transferring data at around 7,200 characters/second, magnetic tapes store data in sequential order, which also can be accessed only in a sequential order. The magnetic tape’s storage density and feasibility offered it a ready-made advantage against punched storage techniques. Even through the ’90s, as floppy disks and compact discs were taking over the market, magnetic tapes held a fan-like following among large corporations for large-scale data storage. By the turn of the century, as solid state data storage took over, magnetic tapes lost hold with them too.
Floppy Disk
The floppy disk memory technique uses a thin plastic-coated film covered with magnetic material. It is covered with a protective plastic cover. Initially developed by IBM as inexpensive microcode feeders in 1967, floppy disks were made commercially available in 1971 to the public.

Floppy disks began as giant 8-inch diskettes, and eventually evolved into 5¼-inch diskettes, and later 3½-inch diskettes. Floppy disks can easily be termed the most popular data storage forms ever, considering they were launched in 1971 and were broadly used right up to the late 2000s. The fact that their availability coincided with the rise of popularity of personal computers among the general public can be attributed as one of the main reasons behind its immense popularity, the others being portability, feasibility, cost-effectiveness, and the lack of better options.

As of today, no modern machines are integrated with a floppy disk drive, though their popularity amongst low cost data management companies remains intact.
Optical Drives (CD/DVD)

Philips and Sony collaborated in the ’70s on a project to create a new digital audio disc. This collaboration brought together the optical disc drive technologies both the companies were earlier separately working on. Launched in 1982-83, the Compact Disc (CD) eventually went on from being an audio disc to a data storage device.

DVD

The DVD, (originally Digital Video Disc, but later amended to Digital Versatile Disc) format was based on the CD format, and was developed together by Philips, Sony, Toshiba, and Panasonic around the early ’90s. It was launched in 1995 and became an instant success by the virtue of being same size as a CD yet offering almost 4 times its memory space. While data storage isn’t forfended, DVDs are mostly used for audio and video recording/storage/playback purposes.

In the late ’90s, the popularity of CDs took a major three-way hit. While the launch of DVD had already put it out of favor with video enthusiasts, its audio and data storage purposes also waned in lieu of advancing technology. Affordable portable hard disk drives and flash drives drove CDs out as a preferred form of data storage. On the other hand, the easy availability of MP3 players and the legendary rise of Apple’s iPod, practically drove audio CDs out of the market. The DVD too has found successors in the form of HD DVD and Blu-ray discs, and is in the gradual process of being phased out from regular use.
Hard Disk Drives

The dominant technique for storing data in current times, a hard disk consists of rapidly rotating discs with a magnetic head to read and write data. Data can be accessed randomly. HDDs were introduced by IBM (Yes, again IBM!) around the late 1950s for real-time transaction processing machines. A few years later, IBM commercially launched the IBM 1311 model, which was almost as big as a dishwasher, and had the capacity to store about 2 million characters.

Eventually, hard disk drives began to shrink in size and increase in storage capacity. Hard disk drives were sold to PC and Mac users in the ’80s as an external device with a SCSI port on the back of the machines. A series of innovation on part of industry leaders through the ’80s and early ’90s led to the hard disk being integrated inside the CPU. A typical desktop hard disk is 3.5 inches in size, while for laptops it is 2.5 inches.

As portability and convenience became keywords in modern times, hard disks have again become portable. External hard disks typically use the USB plug-and-play mechanism and are very cost-effective. Modern external hard disks can hold up to 2 terabytes of data.

Hard disks seem to be in for the long haul. No better option is in sight for now, and one can easily predict that hard disks should continue to rule as the preferred form of data storage in the years to come.
Flash Drives
A flash drive is a data storage device that uses flash memory for storage purposes. Typical in design, flash drives are light-weight and small in design; and are hence easily portable. Flash drives operate from the power supplied by a computer’s USB port (the port in which they are plugged in). The data on it can be erased and re-programmed as per the user’s requirements. It only has a specific number of erase and write cycles that it can withstand, after which it creates a tendency to lose out on the stored information. Memory cards and USB flash drives are some modes of this type of memory storage. Low cost, minimal power consumption, and portable features make flash drives extremely desirable and popular in modern times.

The concept of computer memory has evolved since the first electronic computer (ENIAC) was set up in 1946 with a primitive read only pre-stored programming mechanism. ENIAC used function tables for storing instructions. Its maximum storage capacity was 600 two-hundred digit decimal instructions. The way data is stored today and the volumes in which it can be stored today is like a million miles ahead of that.

Memory management has become an important concept in every computer programmer’s textbook. Corporations and computer scientists keep researching for newer, simpler, easier, and cost-effective methods of memory storage that can hold larger and larger capacity of data than what is currently possible. Computer memory and its evolution is a constant process, much like the rest of technology. It has changed multifold over the last few decades; expect it to change multifold in the decades to come.
The storage unit has four main types of memory units. They are:

  1. Cache Memory,
  2. Random Access Memory,
  3. Hard Disk,
  4. Virtual memory

The Memory Hierarchy:

The term memory hierarchy is used in computer architecture when discussing performance issues in computer architectural design, algorithm predictions, and the lower level programming constructs such as involving locality of reference. A “memory hierarchy” in computer storage distinguishes each level in the “hierarchy” by response time. Since response time, complexity, and capacity are related, the levels may also be distinguished by the controlling technology.

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Figure: the figure of Memory Hierarchy in Computer

4.Central Processing Unit(CPU):     

A central processing unit (CPU) (formerly also referred to as a central processor unit) is the hardware within a computer that carries out the instructions of a computer program by performing the basic arithmetical, logical, and input/output operations of the system. The term has been in use in the computer industry at least since the early 1960s. The form, design, and implementation of CPUs have changed over the course of their history, but their fundamental operation remains much the same.

A computer can have more than one CPU; this is called multiprocessing. All modern CPUs are microprocessors, meaning contained on a single chip. Some integrated circuits (ICs) can contain multiple CPUs on a single chip; those ICs are called multi-core processors. An IC containing a CPU can also contain peripheral devices, and other components of a computer system; this is called a system on a chip (SoC).

Two typical components of a CPU are the arithmetic logic unit (ALU), which performs arithmetic and logical operations, and the control unit (CU), which extracts instructions from memory and decodes and executes them, calling on the ALU when necessary.

Not all computational systems rely on a central processing unit. An array processor or vector processor has multiple parallel computing elements, with no one unit considered the “center”. In the distributed computing model, problems are solved by a distributed interconnected set of processors.

History

Computers such as the ENIAC had to be physically rewired to perform different tasks, which caused these machines to be called “fixed-program computers”. Since the term “CPU” is generally defined as a device for software (computer program) execution, the earliest devices that could rightly be called CPUs came with the advent of the stored-program computer.

The idea of a stored-program computer was already present in the design of J. Presper Eckert and John William Mauchly’s ENIAC, but was initially omitted so that it could be finished sooner. On June 30, 1945, before ENIAC was made, mathematician John von Neumann distributed the paper entitled First Draft of a Report on the EDVAC. It was the outline of a stored-program computer that would eventually be completed in August 1949. EDVAC was designed to perform a certain number of instructions (or operations) of various types. Significantly, the programs written for EDVAC were to be stored in high-speed computer memory rather than specified by the physical wiring of the computer. This overcame a severe limitation of ENIAC, which was the considerable time and effort required to reconfigure the computer to perform a new task. With von Neumann’s design, the program, or software, that EDVAC ran could be changed simply by changing the contents of the memory. EDVAC, however, was not the first stored-program computer; the Manchester Small-Scale Experimental Machine, a small prototype stored-program computer, ran its first program on 21 June 1948 and the Manchester Mark 1 ran its first program during the night of 16–17 June 1949.

Early CPUs were custom-designed as a part of a larger, sometimes one-of-a-kind, computer. However, this method of designing custom CPUs for a particular application has largely given way to the development of mass-produced processors that are made for many purposes. This standardization began in the era of discrete transistor mainframes and minicomputers and has rapidly accelerated with the popularization of the integrated circuit (IC). The IC has allowed increasingly complex CPUs to be designed and manufactured to tolerances on the order of nanometers. Both the miniaturization and standardization of CPUs have increased the presence of digital devices in modern life far beyond the limited application of dedicated computing machines. Modern microprocessors appear in everything from automobiles to cell phones and children’s toys.

While von Neumann is most often credited with the design of the stored-program computer because of his design of EDVAC, others before him, such as Konrad Zuse, had suggested and implemented similar ideas. The so-called Harvard architecture of the Harvard Mark I, which was completed before EDVAC, also utilized a stored-program design using punched paper tape rather than electronic memory. The key difference between the von Neumann and Harvard architectures is that the latter separates the storage and treatment of CPU instructions and data, while the former uses the same memory space for both. Most modern CPUs are primarily von Neumann in design, but CPUs with the Harvard architecture are seen as well, especially in embedded applications; for instance, the Atmel AVR microcontrollers are Harvard architecture processors.

Relays and vacuum tubes (thermionic valves) were commonly used as switching elements; a useful computer requires thousands or tens of thousands of switching devices. The overall speed of a system is dependent on the speed of the switches. Tube computers like EDVAC tended to average eight hours between failures, whereas relay computers like the (slower, but earlier) Harvard Mark I failed very rarely. In the end, tube-based CPUs became dominant because the significant speed advantages afforded generally outweighed the reliability problems. Most of these early synchronous CPUs ran at low clock rates compared to modern microelectronic designs (see below for a discussion of clock rate). Clock signal frequencies ranging from 100 KHz to 4 MHz were very common at this time, limited largely by the speed of the switching devices they were built with.

Transistor and integrated circuit CPUs

The design complexity of CPUs increased as various technologies facilitated building smaller and more reliable electronic devices. The first such improvement came with the advent of the transistor. Transistorized CPUs during the 1950s and 1960s no longer had to be built out of bulky, unreliable, and fragile switching elements like vacuum tubes and electrical relays. With this improvement more complex and reliable CPUs were built onto one or several printed circuit boards containing discrete (individual) components.

During this period, a method of manufacturing many interconnected transistors in a compact space was developed. The integrated circuit (IC) allowed a large number of transistors to be manufactured on a single semiconductor-based die, or “chip”. At first only very basic non-specialized digital circuits such as NOR gates were miniaturized into ICs. CPUs based upon these “building block” ICs are generally referred to as “small-scale integration” (SSI) devices. SSI ICs, such as the ones used in the Apollo guidance computer, usually contained up to a few score transistors. To build an entire CPU out of SSI ICs required thousands of individual chips, but still consumed much less space and power than earlier discrete transistor designs. As microelectronic technology advanced, an increasing number of transistors were placed on ICs, thus decreasing the quantity of individual ICs needed for a complete CPU. MSI and LSI (medium- and large-scale integration) ICs increased transistor counts to hundreds, and then thousands.

In 1964 IBM introduced its System/360 computer architecture which was used in a series of computers that could run the same programs with different speed and performance. This was significant at a time when most electronic computers were incompatible with one another, even those made by the same manufacturer. To facilitate this improvement, IBM utilized the concept of a microprogram (often called “microcode”), which still sees widespread usage in modern CPUs.[5] The System/360 architecture was so popular that it dominated the mainframe computer market for decades and left a legacy that is still continued by similar modern computers like the IBM zSeries. In the same year (1964), Digital Equipment Corporation (DEC) introduced another influential computer aimed at the scientific and research markets, the PDP-8. DEC would later introduce the extremely popular PDP-11 line that originally was built with SSI ICs but was eventually implemented with LSI components once these became practical. In stark contrast with its SSI and MSI predecessors, the first LSI implementation of the PDP-11 contained a CPU composed of only four LSI integrated circuits.

Transistor-based computers had several distinct advantages over their predecessors. Aside from facilitating increased reliability and lower power consumption, transistors also allowed CPUs to operate at much higher speeds because of the short switching time of a transistor in comparison to a tube or relay. Thanks to both the increased reliability as well as the dramatically increased speed of the switching elements (which were almost exclusively transistors by this time), CPU clock rates in the tens of megahertz were obtained during this period. Additionally while discrete transistor and IC CPUs were in heavy usage, new high-performance designs like SIMD (Single Instruction Multiple Data) vector processors began to appear. These early experimental designs later gave rise to the era of specialized supercomputers like those made by Cray Inc.

 

Microprocessors

In the 1970s the fundamental inventions by Federico Faggin (Silicon Gate MOS ICs with self-aligned gates along with his new random logic design methodology) changed the design and implementation of CPUs forever. Since the introduction of the first commercially available microprocessor (the Intel 4004) in 1970, and the first widely used microprocessor (the Intel 8080) in 1974, this class of CPUs has almost completely overtaken all other central processing unit implementation methods. Mainframe and minicomputer manufacturers of the time launched proprietary IC development programs to upgrade their older computer architectures, and eventually produced instruction set compatible microprocessors that were backward-compatible with their older hardware and software. Combined with the advent and eventual success of the ubiquitous personal computer, the term CPU is now applied almost exclusivelyto microprocessors. Several CPUs (denoted ‘cores’) can be combined in a single processing chip.

Previous generations of CPUs were implemented as discrete components and numerous small integrated circuits (ICs) on one or more circuit boards. Microprocessors, on the other hand, are CPUs manufactured on a very small number of ICs; usually just one. The overall smaller CPU size as a result of being implemented on a single die means faster switching time because of physical factors like decreased gate parasitic capacitance. This has allowed synchronous microprocessors to have clock rates ranging from tens of megahertz to several GigaHertz. Additionally, as the ability to construct exceedingly small transistors on an IC has increased, the complexity and number of transistors in a single CPU has increased many fold. This widely observed trend is described by Moore’s law, which has proven to be a fairly accurate predictor of the growth of CPU (and other IC) complexity.

While the complexity, size, construction, and general form of CPUs have changed enormously since 1950, it is notable that the basic design and function has not changed much at all. Almost all common CPUs today can be very accurately described as von Neumann stored-program machines. As the aforementioned Moore’s law continues to hold true, concerns have arisen about the limits of integrated circuit transistor technology. Extreme miniaturization of electronic gates is causing the effects of phenomena like electromigration and sub threshold leakage to become much more significant. These newer concerns are among the many factors causing researchers to investigate new methods of computing such as the quantum computer, as well as to expand the usage of parallelism and other methods that extend the usefulness of the classical von Neumann model.

Operation

The fundamental operation of most CPUs, regardless of the physical form they take, is to execute a sequence of stored instructions called a program. The instructions are kept in some kind of computer memory. There are four steps that nearly all CPUs use in their operation: fetch, decode, execute, and writeback.

The first step, fetch, involves retrieving an instruction (which is represented by a number or sequence of numbers) from program memory. Its location (address) in program memory is determined by a program counter (PC), which stores a number that identifies the address of the next instruction to be fetched. After an instruction is fetched, the PC is incremented by the length of the instruction word in terms of memory units. Often, the instruction to be fetched must be retrieved from relatively slow memory, causing the CPU to stall while waiting for the instruction to be returned. This issue is largely addressed in modern processors by caches and pipeline architectures.

The instruction that the CPU fetches from memory is used to determine what the CPU is to do. In the decode step, the instruction is broken up into parts that have significance to other portions of the CPU. The way in which the numerical instruction value is interpreted is defined by the CPU’s instruction set architecture (ISA). Often, one group of numbers in the instruction, called the opcode, indicates which operation to perform. The remaining parts of the number usually provide information required for that instruction, such as operands for an addition operation. Such operands may be given as a constant value (called an immediate value), or as a place to locate a value: a register or a memory address, as determined by some addressing mode. In older designs the portions of the CPU responsible for instruction decoding were unchangeable hardware devices. However, in more abstract and complicated CPUs and ISAs, a microprogram is often used to assist in translating instructions into various configuration signals for the CPU. This microprogram is sometimes rewritable so that it can be modified to change the way the CPU decodes instructions even after it has been manufactured.

After the fetch and decode steps, the execute step is performed. During this step, various portions of the CPU are connected so they can perform the desired operation. If, for instance, an addition operation was requested, the arithmetic logic unit (ALU) will be connected to a set of inputs and a set of outputs. The inputs provide the numbers to be added, and the outputs will contain the final sum. The ALU contains the circuitry to perform simple arithmetic and logical operations on the inputs (like addition and bitwise operations). If the addition operation produces a result too large for the CPU to handle, an arithmetic overflow flag in a flags register may also be set.

The final step, writeback, simply “writes back” the results of the execute step to some form of memory. Very often the results are written to some internal CPU register for quick access by subsequent instructions. In other cases results may be written to slower, but cheaper and larger, main memory. Some types of instructions manipulate the program counter rather than directly produce result data. These are generally called “jumps” and facilitate behavior like loops, conditional program execution (through the use of a conditional jump), and functions in programs. Many instructions will also change the state of digits in a “flags” register. These flags can be used to influence how a program behaves, since they often indicate the outcome of various operations. For example, one type of “compare” instruction considers two values and sets a number in the flags register according to which one is greater. This flag could then be used by a later jump instruction to determine program flow.

After the execution of the instruction and writeback of the resulting data, the entire process repeats, with the next instruction cycle normally fetching the next-in-sequence instruction because of the incremented value in the program counter. If the completed instruction was a jump, the program counter will be modified to contain the address of the instruction that was jumped to, and program execution continues normally. In more complex CPUs than the one described here, multiple instructions can be fetched, decoded, and executed simultaneously. This section describes what is generally referred to as the “classic RISC pipeline”, which in fact is quite common among the simple CPUs used in many electronic devices (often called microcontroller). It largely ignores the important role of CPU cache, and therefore the access stage of the pipeline.

Design and implementation

The basic concept of a CPU is as follows:

Hardwired into a CPU’s design is a list of basic operations it can perform, called an instruction set. Such operations may include adding or subtracting two numbers, comparing numbers, or jumping to a different part of a program. Each of these basic operations is represented by a particular sequence of bits; this sequence is called the opcode for that particular operation. Sending a particular opcode to a CPU will cause it to perform the operation represented by that opcode. To execute an instruction in a computer program, the CPU uses the opcode for that instruction as well as its arguments (for instance the two numbers to be added, in the case of an addition operation). A computer program is therefore a sequence of instructions, with each instruction including an opcode and that operation’s arguments.

The actual mathematical operation for each instruction is performed by a subunit of the CPU known as the arithmetic logic unit or ALU. In addition to using its ALU to perform operations, a CPU is also responsible for reading the next instruction from memory, reading data specified in arguments from memory, and writing results to memory.

In many CPU designs, an instruction set will clearly differentiate between operations that load data from memory, and those that perform math. In this case the data loaded from memory is stored in registers, and a mathematical operation takes no arguments but simply performs the math on the data in the registers and writes it to a new register, whose value a separate operation may then write to memory.

Control unit

The control unit of the CPU contains circuitry that uses electrical signals to direct the entire computer system to carry out stored program instructions. The control unit does not execute program instructions; rather, it directs other parts of the system to do so. The control unit must communicate with both the arithmetic/logic unit and memory.

Integer range

The way a CPU represents numbers is a design choice that affects the most basic ways in which the device functions. Some early digital computers used an electrical model of the common decimal (base ten) numeral system to represent numbers internally. A few other computers have used more exotic numeral systems like ternary (base three). Nearly all modern CPUs represent numbers in binary form, with each digit being represented by some two-valued physical quantity such as a “high” or “low” voltage.

Related to number representation is the size and precision of numbers that a CPU can represent. In the case of a binary CPU, a bit refers to one significant place in the numbers a CPU deals with. The number of bits (or numeral places) a CPU uses to represent numbers is often called “word size”, “bit width”, “data path width”, or “integer precision” when dealing with strictly integer numbers (as opposed to floating point). This number differs between architectures, and often within different parts of the very same CPU. For example, an 8-bit CPU deals with a range of numbers that can be represented by eight binary digits (each digit having two possible values), that is, 28 or 256 discrete numbers. In effect, integer size sets a hardware limit on the range of integers the software run by the CPU can utilize.

Integer range can also affect the number of locations in memory the CPU can address (locate). For example, if a binary CPU uses 32 bits to represent a memory address, and each memory address represents one octet (8 bits), the maximum quantity of memory that CPU can address is 232 octets, or 4 GiB. This is a very simple view of CPU address space, and many designs use more complex addressing methods like paging to locate more memory than their integer range would allow with a flat address space.

Higher levels of integer range require more structures to deal with the additional digits, and therefore more complexity, size, power usage, and general expense. It is not at all uncommon, therefore, to see 4- or 8-bit microcontrollers used in modern applications, even though CPUs with much higher range (such as 16, 32, 64, even 128-bit) are available. The simpler microcontrollers are usually cheaper, use less power, and therefore generate less heat, all of which can be major design considerations for electronic devices. However, in higher-end applications, the benefits afforded by the extra range (most often the additional address space) are more significant and often affect design choices. To gain some of the advantages afforded by both lower and higher bit lengths, many CPUs are designed with different bit widths for different portions of the device. For example, the IBM System/370 used a CPU that was primarily 32 bit, but it used 128-bit precision inside its floating point units to facilitate greater accuracy and range in floating point numbers.[5] Many later CPU designs use similar mixed bit width, especially when the processor is meant for general-purpose usage where a reasonable balance of integer and floating point capability is required.

 

Clock rate

The clock rate is the speed at which a microprocessor executes instructions. Every computer contains an internal clock that regulates the rate at which instructions are executed and synchronizes all the various computer components. The faster the clock, the more instructions the CPU can execute per second.

Most CPUs, and indeed most sequential logic devices, are synchronous in nature.[h] That is, they are designed with, and operate under, assumptions about a synchronization signal. This signal, known as a clock signal, usually takes the form of a periodic square wave. By calculating the maximum time that electrical signals can move in various branches of a CPU’s many circuits, the designers can select an appropriate period for the clock signal.

This period must be longer than the amount of time it takes for a signal to move, or propagate, in the worst-case scenario. In setting the clock period to a value well above the worst-case propagation delay, it is possible to design the entire CPU and the way it moves data around the “edges” of the rising and falling clock signal. This has the advantage of simplifying the CPU significantly, both from a design perspective and a component-count perspective. However, it also carries the disadvantage that the entire CPU must wait on its slowest elements, even though some portions of it are much faster. This limitation has largely been compensated for by various methods of increasing CPU parallelism (see below).

However, architectural improvements alone do not solve all of the drawbacks of globally synchronous CPUs. For example, a clock signal is subject to the delays of any other electrical signal. Higher clock rates in increasingly complex CPUs make it more difficult to keep the clock signal in phase (synchronized) throughout the entire unit. This has led many modern CPUs to require multiple identical clock signals to be provided to avoid delaying a single signal significantly enough to cause the CPU to malfunction. Another major issue as clock rates increase dramatically is the amount of heat that is dissipated by the CPU. The constantly changing clock causes many components to switch regardless of whether they are being used at that time. In general, a component that is switching uses more energy than an element in a static state. Therefore, as clock rate increases, so does energy consumption, causing the CPU to require more heat dissipation in the form of CPU cooling solutions.

One method of dealing with the switching of unneeded components is called clock gating, which involves turning off the clock signal to unneeded components (effectively disabling them). However, this is often regarded as difficult to implement and therefore does not see common usage outside of very low-power designs. One notable late CPU design that uses extensive clock gating to reduce the power requirements of the videogame console is that of the IBM PowerPC-based Xbox 360.[8] Another method of addressing some of the problems with a global clock signal is the removal of the clock signal altogether. While removing the global clock signal makes the design process considerably more complex in many ways, asynchronous (or clockless) designs carry marked advantages in power consumption and heat dissipation in comparison with similar synchronous designs. While somewhat uncommon, entire asynchronous CPUs have been built without utilizing a global clock signal. Two notable examples of this are the ARM compliant AMULET and the MIPS R3000 compatible MiniMIPS. Rather than totally removing the clock signal, some CPU designs allow certain portions of the device to be asynchronous, such as using asynchronous ALUs in conjunction with superscalar pipelining to achieve some arithmetic performance gains. While it is not altogether clear whether totally asynchronous designs can perform at a comparable or better level than their synchronous counterparts, it is evident that they do at least excel in simpler math operations. This, combined with their excellent power consumption and heat dissipation properties, makes them very suitable for embedded computers.

Parallelism

The description of the basic operation of a CPU offered in the previous section describes the simplest form that a CPU can take. This type of CPU, usually referred to as subscalar, operates on and executes one instruction on one or two pieces of data at a time.

This process gives rise to an inherent inefficiency in subscalar CPUs. Since only one instruction is executed at a time, the entire CPU must wait for that instruction to complete before proceeding to the next instruction. As a result, the subscalar CPU gets “hung up” on instructions which take more than one clock cycle to complete execution. Even adding a second execution unit (see below) does not improve performance much; rather than one pathway being hung up, now two pathways are hung up and the number of unused transistors is increased. This design, wherein the CPU’s execution resources can operate on only one instruction at a time, can only possibly reach scalar performance (one instruction per clock). However, the performance is nearly always subscalar (less than one instruction per cycle).

Attempts to achieve scalar and better performance have resulted in a variety of design methodologies that cause the CPU to behave less linearly and more in parallel. When referring to parallelism in CPUs, two terms are generally used to classify these design techniques. Instruction level parallelism (ILP) seeks to increase the rate at which instructions are executed within a CPU (that is, to increase the utilization of on-die execution resources), and thread level parallelism (TLP) purposes to increase the number of threads (effectively individual programs) that a CPU can execute simultaneously. Each methodology differs both in the ways in which they are implemented, as well as the relative effectiveness they afford in increasing the CPU’s performance for an application.[i]

Instruction level parallelism

One of the simplest methods used to accomplish increased parallelism is to begin the first steps of instruction fetching and decoding before the prior instruction finishes executing. This is the simplest form of a technique known as instruction pipelining, and is utilized in almost all modern general-purpose CPUs. Pipelining allows more than one instruction to be executed at any given time by breaking down the execution pathway into discrete stages. This separation can be compared to an assembly line, in which an instruction is made more complete at each stage until it exits the execution pipeline and is retired.

Pipelining does, however, introduce the possibility for a situation where the result of the previous operation is needed to complete the next operation; a condition often termed data dependency conflict. To cope with this, additional care must be taken to check for these sorts of conditions and delay a portion of the instruction pipeline if this occurs. Naturally, accomplishing this requires additional circuitry, so pipelined processors are more complex than subscalar ones (though not very significantly so). A pipelined processor can become very nearly scalar, inhibited only by pipeline stalls (an instruction spending more than one clock cycle in a stage).

Further improvement upon the idea of instruction pipelining led to the development of a method that decreases the idle time of CPU components even further. Designs that are said to be superscalar include a long instruction pipeline and multiple identical execution units.[10] In a superscalar pipeline, multiple instructions are read and passed to a dispatcher, which decides whether or not the instructions can be executed in parallel (simultaneously). If so they are dispatched to available execution units, resulting in the ability for several instructions to be executed simultaneously. In general, the more instructions a superscalar CPU is able to dispatch simultaneously to waiting execution units, the more instructions will be completed in a given cycle.

Most of the difficulty in the design of a superscalar CPU architecture lies in creating an effective dispatcher. The dispatcher needs to be able to quickly and correctly determine whether instructions can be executed in parallel, as well as dispatch them in such a way as to keep as many execution units busy as possible. This requires that the instruction pipeline is filled as often as possible and gives rise to the need in superscalar architectures for significant amounts of CPU cache. It also makes hazard-avoiding techniques like branch prediction, speculative execution, and out-of-order execution crucial to maintaining high levels of performance. By attempting to predict which branch (or path) a conditional instruction will take, the CPU can minimize the number of times that the entire pipeline must wait until a conditional instruction is completed. Speculative execution often provides modest performance increases by executing portions of code that may not be needed after a conditional operation completes. Out-of-order execution somewhat rearranges the order in which instructions are executed to reduce delays due to data dependencies. Also in case of Single Instructions Multiple Data — a case when a lot of data from the same type has to be processed, modern processors can disable parts of the pipeline so that when a single instruction is executed many times, the CPU skips the fetch and decode phases and thus greatly increases performance on certain occasions, especially in highly monotonous program engines such as video creation software and photo processing.

In the case where a portion of the CPU is superscalar and part is not, the part which is not suffers a performance penalty due to scheduling stalls. The Intel P5 Pentium had two superscalar ALUs which could accept one instruction per clock each, but its FPU could not accept one instruction per clock. Thus the P5 was integer superscalar but not floating point superscalar. Intel’s successor to the P5 architecture, P6, added superscalar capabilities to its floating point features, and therefore afforded a significant increase in floating point instruction performance.

Both simple pipelining and superscalar design increase a CPU’s ILP by allowing a single processor to complete execution of instructions at rates surpassing one instruction per cycle (IPC).[j] Most modern CPU designs are at least somewhat superscalar, and nearly all general purpose CPUs designed in the last decade are superscalar. In later years some of the emphasis in designing high-ILP computers has been moved out of the CPU’s hardware and into its software interface, or ISA. The strategy of the very long instruction word (VLIW) causes some ILP to become implied directly by the software, reducing the amount of work the CPU must perform to boost ILP and thereby reducing the design’s complexity.

Thread-level parallelism

Another strategy of achieving performance is to execute multiple programs or threads in parallel. This area of research is known as parallel computing. In Flynn’s taxonomy, this strategy is known as Multiple Instructions-Multiple Data or MIMD.

One technology used for this purpose was multiprocessing (MP). The initial flavor of this technology is known as symmetric multiprocessing (SMP), where a small number of CPUs share a coherent view of their memory system. In this scheme, each CPU has additional hardware to maintain a constantly up-to-date view of memory. By avoiding stale views of memory, the CPUs can cooperate on the same program and programs can migrate from one CPU to another. To increase the number of cooperating CPUs beyond a handful, schemes such as non-uniform memory access (NUMA) and directory-based coherence protocols were introduced in the 1990s. SMP systems are limited to a small number of CPUs while NUMA systems have been built with thousands of processors. Initially, multiprocessing was built using multiple discrete CPUs and boards to implement the interconnect between the processors. When the processors and their interconnect are all implemented on a single silicon chip, the technology is known as a multi-core processor.

It was later recognized that finer-grain parallelism existed with a single program. A single program might have several threads (or functions) that could be executed separately or in parallel. Some of the earliest examples of this technology implemented input/output processing such as direct memory access as a separate thread from the computation thread. A more general approach to this technology was introduced in the 1970s when systems were designed to run multiple computation threads in parallel. This technology is known as multi-threading (MT). This approach is considered more cost-effective than multiprocessing, as only a small number of components within a CPU is replicated to support MT as opposed to the entire CPU in the case of MP. In MT, the execution units and the memory system including the caches are shared among multiple threads. The downside of MT is that the hardware support for multithreading is more visible to software than that of MP and thus supervisor software like operating systems have to undergo larger changes to support MT. One type of MT that was implemented is known as block multithreading, where one thread is executed until it is stalled waiting for data to return from external memory. In this scheme, the CPU would then quickly switch to another thread which is ready to run, the switch often done in one CPU clock cycle, such as the UltraSPARC Technology. Another type of MT is known as simultaneous multithreading, where instructions of multiple threads are executed in parallel within one CPU clock cycle.

For several decades from the 1970s to early 2000s, the focus in designing high performance general purpose CPUs was largely on achieving high ILP through technologies such as pipelining, caches, superscalar execution, out-of-order execution, etc. This trend culminated in large, power-hungry CPUs such as the Intel Pentium 4. By the early 2000s, CPU designers were thwarted from achieving higher performance from ILP techniques due to the growing disparity between CPU operating frequencies and main memory operating frequencies as well as escalating CPU power dissipation owing to more esoteric ILP techniques.

CPU designers then borrowed ideas from commercial computing markets such as transaction processing, where the aggregate performance of multiple programs, also known as throughput computing, was more important than the performance of a single thread or program.

This reversal of emphasis is evidenced by the proliferation of dual and multiple core CMP (chip-level multiprocessing) designs and notably, Intel’s newer designs resembling its less superscalar P6 architecture. Late designs in several processor families exhibit CMP, including the x86-64 Opteron and Athlon 64 X2, the SPARC UltraSPARC T1, IBM POWER4 and POWER5, as well as several video game console CPUs like the Xbox 360’s triple-core PowerPC design, and the PS3’s 7-core Cell microprocessor.

Data parallelism

A less common but increasingly important paradigm of CPUs (and indeed, computing in general) deals with data parallelism. The processors discussed earlier are all referred to as some type of scalar device.[k] As the name implies, vector processors deal with multiple pieces of data in the context of one instruction. This contrasts with scalar processors, which deal with one piece of data for every instruction. Using Flynn’s taxonomy, these two schemes of dealing with data are generally referred to as SIMD (single instruction, multiple data) and SISD (single instruction, single data), respectively. The great utility in creating CPUs that deal with vectors of data lies in optimizing tasks that tend to require the same operation (for example, a sum or a dot product) to be performed on a large set of data. Some classic examples of these types of tasks are multimedia applications (images, video, and sound), as well as many types of scientific and engineering tasks. Whereas a scalar CPU must complete the entire process of fetching, decoding, and executing each instruction and value in a set of data, a vector CPU can perform a single operation on a comparatively large set of data with one instruction. Of course, this is only possible when the application tends to require many steps which apply one operation to a large set of data.

Most early vector CPUs, such as the Cray-1, were associated almost exclusively with scientific research and cryptography applications. However, as multimedia has largely shifted to digital media, the need for some form of SIMD in general-purpose CPUs has become significant. Shortly after inclusion of floating point execution units started to become commonplace in general-purpose processors, specifications for and implementations of SIMD execution units also began to appear for general-purpose CPUs. Some of these early SIMD specifications like HP’s Multimedia Acceleration eXtensions (MAX) and Intel’s MMX were integer-only. This proved to be a significant impediment for some software developers, since many of the applications that benefit from SIMD primarily deal with floating point numbers. Progressively, these early designs were refined and remade into some of the common, modern SIMD specifications, which are usually associated with one ISA. Some notable modern examples are Intel’s SSE and the PowerPC-related AltiVec (also known as VMX).[l]

Performance

The performance or speed of a processor depends on, among many other factors, the clock rate (generally given in multiples of hertz) and the instructions per clock (IPC), which together are the factors for the instructions per second (IPS) that the CPU can perform.[11] Many reported IPS values have represented “peak” execution rates on artificial instruction sequences with few branches, whereas realistic workloads consist of a mix of instructions and applications, some of which take longer to execute than others. The performance of the memory hierarchy also greatly affects processor performance, an issue barely considered in MIPS calculations. Because of these problems, various standardized tests, often called “benchmarks” for this purpose—such as SPECint – have been developed to attempt to measure the real effective performance in commonly used applications.

Processing performance of computers is increased by using multi-core processors, which essentially is plugging two or more individual processors (called cores in this sense) into one integrated circuit.[12] Ideally, a dual core processor would be nearly twice as powerful as a single core processor. In practice, however, the performance gain is far less, only about 50%,[12] due to imperfect software algorithms and implementation. Increasing the number of cores in a processor (i.e. dual-core, quad-core, etc.) increases the workload that can be handled. This means that the processor can now handle numerous asynchronous events, interrupts, etc. which can take a toll on the CPU (Central Processing Unit) when overwhelmed. These cores can be thought of as different floors in a processing plant, with each floor handling a different task. Sometimes, these cores will handle the same tasks as cores adjacent to them if a single core is not enough to handle the information.

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CONTRIBUTOR

Fatematuj Jahara

Student ID- 142015001

Department of Electronics and Telecommunication Engineering

University of Liberal Arts Bangladesh

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