User:Ky1204/Processor (computing): Difference between revisions

 

Line 2: Line 2:

In [[computing]] and [[computer science]], a ”’processor”’ or ”’processing unit”’ is an electrical component ([[Circuit (computer science)|digital circuit]]) that performs operations on an external data source, usually [[Memory (computing)|memory]] or some other data stream.<ref>{{Cite book |last=Wienand |first=Ian |title=Computer Science from the Bottom Up |date=2004-01-01 |year= |publication-date= |pages=30-138 |language=en}}</ref> The term is frequently used to refer to the [[central processing unit]] (CPU), the main processor in a system. It can also refer to other specialized processors such as [[graphics processing units]] (GPU), [[Quantum processing unit|quantum processing units]] (QPU), and [[Digital signal processor|digital signal processors]] (DSP).

In [[computing]] and [[computer science]], a ”’processor”’ or ”’processing unit”’ is an electrical component ([[Circuit (computer science)|digital circuit]]) that performs operations on an external data source, usually [[Memory (computing)|memory]] or some other data stream.<ref>{{Cite book |last=Wienand |first=Ian |title=Computer Science from the Bottom Up |date=2004-01-01 |year= |publication-date= |pages=30-138 |language=en}}</ref> The term is frequently used to refer to the [[central processing unit]] (CPU), the main processor in a system. It can also refer to other specialized processors such as [[graphics processing units]] (GPU), [[Quantum processing unit|quantum processing units]] (QPU), and [[Digital signal processor|digital signal processors]] (DSP).

== Heading 1: History [Andrew] ==

== History ==

The word “processor” has been applied to computers since at least the early 1950’s. Early computers utilized complex arrays of vacuum tubes. These early computers were large, expensive,  and power intensive, limiting their use to large organizations. The [[Ferranti Mark 1]] represents one of the earliest processors in the modern sense, as the first general-purpose computer capable of storing programs.

The word “processor” has been applied to computers since at least the early 1950’s. Early computers utilized complex arrays of vacuum tubes. These early computers were large, expensive,  and power intensive, limiting their use to large organizations. The [[Ferranti Mark 1]] represents one of the earliest processors in the modern sense, as the first general-purpose computer capable of storing programs.

Line 22: Line 22:

When the final prototype of the processor is created, it is implemented into different hardwares and softwares. Hardware implementation requires high-level modeling such as converting functional blocks into a [[hardware description language]] and arranging the functional blocks on the processor chip to optimize its performance and area. Software implementation is the hardest part of the design process. This process requires [[debugging]] hardware and software issues that prevent the processor to run cohesively within the software.<ref>{{Cite book |last=Nurmi |first=Jari |title=Processor Design System-On-Chip Computing for ASICs and FPGAs |date= |publisher=Springer |year=2007 |isbn=978-1-4020-5529-4 |location=P.O. Box 17, 3300 AA Dordrecht, The Netherlands. |publication-date= |pages=69-82 |language=English}}</ref>

When the final prototype of the processor is created, it is implemented into different hardwares and softwares. Hardware implementation requires high-level modeling such as converting functional blocks into a [[hardware description language]] and arranging the functional blocks on the processor chip to optimize its performance and area. Software implementation is the hardest part of the design process. This process requires [[debugging]] hardware and software issues that prevent the processor to run cohesively within the software.<ref>{{Cite book |last=Nurmi |first=Jari |title=Processor Design System-On-Chip Computing for ASICs and FPGAs |date= |publisher=Springer |year=2007 |isbn=978-1-4020-5529-4 |location=P.O. Box 17, 3300 AA Dordrecht, The Netherlands. |publication-date= |pages=69-82 |language=English}}</ref>

== Heading 3: Types [Karen & Rebecca] ==

== Types ==

Types of processors include Central Processing Unit (CPU), the Graphics Processing Unit (GPU), the Digital Signal Processor (DSP), and the Quantum Processing Unit (QPU).

Types of processors include Central Processing Unit (CPU), the Graphics Processing Unit (GPU), the Digital Signal Processor (DSP), and the Quantum Processing Unit (QPU).

In computing and computer science, a processor or processing unit is an electrical component (digital circuit) that performs operations on an external data source, usually memory or some other data stream.^[1] The term is frequently used to refer to the central processing unit (CPU), the main processor in a system. It can also refer to other specialized processors such as graphics processing units (GPU), quantum processing units (QPU), and digital signal processors (DSP).

The word “processor” has been applied to computers since at least the early 1950’s. Early computers utilized complex arrays of vacuum tubes. These early computers were large, expensive,  and power intensive, limiting their use to large organizations. The Ferranti Mark 1 represents one of the earliest processors in the modern sense, as the first general-purpose computer capable of storing programs.

The invention of the transistor brought about rapid innovation in the computer industry. Transistors enabled computer processors to be denser and more power efficient, reducing the size of computers from rooms to something that could fit on a desk.

The first discrete processor comparable to modern devices was the Intel 4004.^[2] The 4004 combined all of the logic circuits required by a computer into a single processor. Sold as a single, discrete chip for general use, it brought computing power to consumer devices such as digital calculators and pinball machines. Modern processors have followed its format, utilizing discretely packaged computer chips with external memory and I/O.

When designing a processor, the non-functional and functional requirements must be established before the design can be applied to hardware or software systems. Many functional requirements are selected from a set of basic instructions or common algorithms used within processing chips. Although a variety of tools are employed to aid processor development, the overall design process remains time-consuming because of the numerous intricacies involved.

The non-functional requirements of a processor refer to its materialistic components. For example, the processor’s silicon area, pin count, and power and energy consumption all affect the design. The cost of manufacturing the processor and its retail price affect those components.

The functional requirements of a processor are its operations and operating environment. The operations are the set of instructions that the processor follows in order to execute its main function. Operations are written using different sets of algorithms, with varying operands. The time a processor spends running, the type of memory subsystem connected to the processor, and the input/output (I/O) are all examples of operating environments. These environments impact how the operations within the functional requirements are written.

Profiling algorithms helps determine critical details within an algorithm that affect its optimality. Profiling between the prototype code and existing processor designs develops understanding of algorithmic applications. Algorithms within existing processors are usually built to optimize slightly different main functions, so not all operations used in this reference may be needed in the prototype design. If the developer relies solely on the reference, the final operating code may be inefficient.

The organizational architecture of a processor refers to the ordered set of basic instructions that allows the processor to complete its task. There are numerous ways the instructions can be organized in order to achieve a certain goal, but the efficiency of the code will vary. Using kernel operations, automated performance estimators, or simulator generators can help the developer determine the most efficient organizational architecture for the processor.

When the final prototype of the processor is created, it is implemented into different hardwares and softwares. Hardware implementation requires high-level modeling such as converting functional blocks into a hardware description language and arranging the functional blocks on the processor chip to optimize its performance and area. Software implementation is the hardest part of the design process. This process requires debugging hardware and software issues that prevent the processor to run cohesively within the software.^[3]

Types of processors include Central Processing Unit (CPU), the Graphics Processing Unit (GPU), the Digital Signal Processor (DSP), and the Quantum Processing Unit (QPU).

Central processing units (CPUs) are the primary processors in computers and are responsible for executing the instructions of programs. They perform general-purpose computing tasks, such as arithmetic logic unit (ALU) that is responsible for all the math and logical comparisons and control unit (CU) that manages the CPU’s activities, rather than being limited to a single specialized function. ^[4]

Most CPUs follow the von Neumann architecture, meaning they contain control unit (CU), arithmetic logic unit (ALU), and registers. The architecture executes programs through a cycle of fetching the instruction from memory and decoding the instruction by using control unit, followed by executing instruction and restoring the result back into memory by using arithmetic logic unit.^[5]

CPUs work closely with main memory, storage devices, and peripherals (keyboard, mouse, etc.) through the motherboard. Together, these components allow the CPU to execute instructions that make the computer operate and applied in consumer electronics, automotive, data analytics, virtualization, and more.^[6]

The graphic processing unit (GPU) is a component present in several devices such as laptops, PCs, smartphones, game consoles, supercomputers, robots, point-of-sale (POS) machines, HPCs, visualization, or high-end games.^[7] They are highly parallel, designed to efficiently perform computer graphics operations, and are useful for gaming, machine learning, video editing, and artificial intelligence.^[7] Although GPUs were originally intended for use in graphics, over time their application domains have expanded, and now incorporate a multitude of tasks including being an important piece of hardware for machine learning.

Digital signal processors (DSPs) are processors in computers and are responsible for processing digital signals to execute high-speed numeric processing application that execute algorithms modelling. ^[8]

DSPs are often more cost-effective than custom hard-ware, and often have an advantage of speed, cost, and energy efficiency due to significantly lower initial development costs that use standardized chips. ^[9]

Because it’s programmable, DSP applications include a wide variety of audio signal processing, speech recognition, telecommunications, sonar, radar, spectral density estimation, statistical signal processing, digital image processing, data compression, video coding, audio coding, image compression, biomedical engineering, and seismology. ^[10]The application of digital computation to signal processing allows for many advantages over analog processing such as data compression, error detection, and correction in transmission.^[11]

The quantum processing unit (QPU) is the core component of a quantum computer. The QPU processes information using qubits which make up the quantum chip and are integrated into high-performance computing (HPC) systems alongside CPUs and GPUs. ^[12] The most common types of quantum processors are superconducting processors, photonic processors, neutral atom quantum processors, trapped ion processors, topological processors, and quantum dot processors, each having variations in its architecture, layout, fidelity, and number of qubits.^[13] These variations are suited for certain tasks such as speed, coherence times, scalability, compatibility, and performance. ^[12] Manufacturers of QPUs include IBM, D-Wave, Google, and Rigetti.^[14]