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Microarchitecture
In computer engineering, microarchitecture, also called computer organization and sometimes abbreviated as µarch or uarch, is the way a given instruction set architecture (ISA), or the ways the PCB is pathed in the Processing unit, is implemented in a particular processor.[1] A given ISA may be implemented with different microarchitectures;[2][3] implementations may vary due to different goals of a given design or due to shifts in technology.[4] Computer architecture
Computer architecture
is the combination of microarchitecture and instruction set.Contents1 Relation to instruction s
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List Of Computer System Manufacturers
The following is a list of notable computer system manufacturers.Contents1 Current 2 Companies that have ceased production 3 See also 4 ReferencesCurrent[edit]ABS Computer
Computer
Technologies (Parent: Newegg) AcerGateway Packard BellAchim ADEK[1] Amiga, Inc.ACube Systems Srl Hyperion EntertainmentAigo AMD Aleutia Alienware
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Load-store Architecture
In computer engineering, a load/store architecture is an instruction set architecture that divides instructions into two categories: memory access (load and store between memory and registers), and ALU operations (which only occur between registers).[1]:9-12 RISC instruction set architectures such as PowerPC, SPARC, RISC-V, ARM, and MIPS are load/store architectures.[1]:9-12 For instance, in a load/store approach both operands and destination for an ADD operation must be in registers
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Digital Signal Processor
A digital signal processor (DSP) is a specialized microprocessor (or a SIP block), with its architecture optimized for the operational needs of digital signal processing.[1][2] The goal of DSPs is usually to measure, filter or compress continuous real-world analog signals
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Floating Point Unit
A floating-point unit (FPU, colloquially a math coprocessor) is a part of a computer system specially designed to carry out operations on floating point numbers.[1] Typical operations are addition, subtraction, multiplication, division, square root, and bitshifting. Some systems (particularly older, microcode-based architectures) can also perform various transcendental functions such as exponential or trigonometric calculations, though in most modern processors these are done with software library routines. In general purpose computer architectures, one or more FPUs may be integrated as execution units within the central processing unit; however many embedded processors do not have hardware support for floating-point operations (while they increasingly have them as standard, at least 32-bit
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SIMD
Single instruction, multiple data (SIMD), is a class of parallel computers in Flynn's taxonomy. It describes computers with multiple processing elements that perform the same operation on multiple data points simultaneously. Thus, such machines exploit data level parallelism, but not concurrency: there are simultaneous (parallel) computations, but only a single process (instruction) at a given moment. SIMD
SIMD
is particularly applicable to common tasks such as adjusting the contrast in a digital image or adjusting the volume of digital audio
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Peripheral
A peripheral device is "an ancillary device used to put information into and get information out of the computer."[1] Three categories of peripheral devices exist based on their relationship with the computer:an input device sends data or instructions to the computer, such as a mouse, keyboard, graphics tablet, image scanner, barcode reader, game controller, light pen, light gun, microphone, digital camera, webcam, dance pad, and read-only memory); an output device provides output from the computer, such as a computer monitor, projector, printer, and computer speaker); and an input/output device performs both input and output functions, such as a computer data storage device (including a disk drive, USB flash drive, memory card, and tape drive) and a touchscreen).Many modern electronic devices, such as digital watches, smartphones, and tablet computers, have interfaces that allow them to be used as computer peripheral devices. See also[edit]Look up peripheral in Wi
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Instruction Cycle
A diagram of the instruction cycle.An instruction cycle (also known as the fetch–decode–execute cycle or the fetch-execute cycle) is the basic operational process of a computer. It is the process by which a computer retrieves a program instruction from its memory, determines what actions the instruction dictates, and carries out those actions. This cycle is repeated continuously by a computer's central processing unit (CPU), from boot-up to when the computer is shut down. In simpler CPUs the instruction cycle is executed sequentially, each instruction being processed before the next one is started
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Cache (computing)
In computing, a cache /kæʃ/ KASH,[1] is a hardware or software component that stores data so future requests for that data can be served faster; the data stored in a cache might be the result of an earlier computation, or the duplicate of data stored elsewhere. A cache hit occurs when the requested data can be found in a cache, while a cache miss occurs when it cannot. Cache hits are served by reading data from the cache, which is faster than recomputing a result or reading from a slower data store; thus, the more requests can be served from the cache, the faster the system performs. To be cost-effective and to enable efficient use of data, caches must be relatively small
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Main Memory
Computer
Computer
data storage, often called storage or memory, is a technology consisting of computer components and recording media that are used to retain digital data. It is a core function and fundamental component of computers.[1]:15–16 The central processing unit (CPU) of a computer is what manipulates data by performing computations. In practice, almost all computers use a storage hierarchy,[1]:468–473 which puts fast but expensive and small storage options close to the CPU
CPU
and slower but larger and cheaper options farther away. Generally the fast volatile technologies (which lose data when off power) are referred to as "memory", while slower persistent technologies are referred to as "storage". In the Von Neumann architecture, the CPU
CPU
consists of two main parts: The control unit and the arithmetic logic unit (ALU)
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Hard Disk
A hard disk drive (HDD), hard disk, hard drive or fixed disk[b] is a data storage device that uses magnetic storage to store and retrieve digital information using one or more rigid rapidly rotating disks (platters) coated with magnetic material. The platters are paired with magnetic heads, usually arranged on a moving actuator arm, which read and write data to the platter surfaces.[2] Data is accessed in a random-access manner, meaning that individual blocks of data can be stored or retrieved in any order and not only sequentially. HDDs are a type of non-volatile storage, retaining stored data even when powered off.[3][4][5] Introduced by IBM
IBM
in 1956,[6] HDDs became the dominant secondary storage device for general-purpose computers by the early 1960s. Continuously improved, HDDs have maintained this position into the modern era of servers and personal computers
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Computer Bus
In computer architecture, a bus[1] (a contraction of the Latin omnibus) is a communication system that transfers data between components inside a computer, or between computers. This expression covers all related hardware components (wire, optical fiber, etc.) and software, including communication protocols.[2] Early computer buses were parallel electrical wires with multiple hardware connections, but the term is now used for any physical arrangement that provides the same logical function as a parallel electrical bus
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Very Long Instruction Word
Very long instruction word (VLIW) refers to instruction set architectures designed to exploit instruction level parallelism (ILP). Whereas conventional central processing units (CPU, processor) mostly allow programs to specify instructions to execute in sequence only, a VLIW processor allows programs to explicitly specify instructions to execute at the same time, concurrently, in parallel. This design is intended to allow higher performance without the complexity inherent in some other designs.Contents1 Overview 2 Motivation 3 Design 4 History 5 Implementations 6 Backward compatibility 7 See also 8 References 9 External linksOverview[edit]This section needs additional citations for verification. Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed
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Instruction Pipeline
In the fourth clock cycle (the green column), the earliest instruction is in MEM stage, and the latest instruction has not yet entered the pipeline. Instruction pipelining
Instruction pipelining
is a technique for implementing instruction-level parallelism within a single processor. Pipelining attempts to keep every part of the processor busy with some instruction by dividing incoming instructions into a series of sequential steps (the eponymous "pipeline") performed by different processor units with different parts of instructions processed in parallel
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Explicitly Parallel Instruction Computing
Explicitly parallel instruction computing (EPIC) is a term coined in 1997 by the HP– Intel
Intel
alliance[1] to describe a computing paradigm that researchers had been investigating since the early 1980s.[2] This paradigm is also called Independence architectures. It was the basis for Intel
Intel
and HP development of the Intel
Intel
Itanium
Itanium
architecture,[3] and HP later asserted that "EPIC" was merely an old term for the Itanium architecture.[4] EPIC permits microprocessors to execute software instructions in parallel by using the compiler, rather than complex on-die circuitry, to control parallel instruction execution
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Data Parallelism
Data parallelism
Data parallelism
is a form of parallelization across multiple processors in parallel computing environments. It focuses on distributing the data across different nodes, which operate on the data in parallel. It can be applied on regular data structures like arrays and matrices by working on each element in parallel. It contrasts to task parallelism as another form of parallelism. A data parallel job on an array of 'n' elements can be divided equally among all the processors. Let us assume we want to sum all the elements of the given array and the time for a single addition operation is Ta time units. In the case of sequential execution, the time taken by the process will be n*Ta time units as it sums up all the elements of an array. On the other hand, if we execute this job as a data parallel job on 4 processors the time taken would reduce to (n/4)*Ta + merging overhead time units
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