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In computing, a pipeline, also known as a data pipeline,is a set of data processing elements connected in series, where the output of one element is the input of the next one. The elements of a pipeline are often executed in parallel or in time-sliced fashion. Some amount of buffer storage is often inserted between elements.
Computer-related pipelines include:
Some operating systems [ example needed ] may provide UNIX-like syntax to string several program runs in a pipeline, but implement the latter as simple serial execution, rather than true pipelining — namely, by waiting for each program to finish before starting the next one.[ citation needed ]
Pipelining is a commonly used concept in everyday life. For example, in the assembly line of a car factory, each specific task — such as installing the engine, installing the hood, and installing the wheels — is often done by a separate work station. The stations carry out their tasks in parallel, each on a different car. Once a car has had one task performed, it moves to the next station. Variations in the time needed to complete the tasks can be accommodated by "buffering" (holding one or more cars in a space between the stations) and/or by "stalling" (temporarily halting the upstream stations), until the next station becomes available.
Suppose that assembling one car requires three tasks that take 20, 10, and 15 minutes, respectively. Then, if all three tasks were performed by a single station, the factory would output one car every 45 minutes. By using a pipeline of three stations, the factory would output the first car in 45 minutes, and then a new one every 20 minutes.
As this example shows, pipelining does not decrease the latency, that is, the total time for one item to go through the whole system. It does however increase the system's throughput, that is, the rate at which new items are processed after the first one.
Since the throughput of a pipeline cannot be better than that of its slowest element, the designer should try to divide the work and resources among the stages so that they all take the same time to complete their tasks. In the car assembly example above, if the three tasks took 15 minutes each, instead of 20, 10, and 15 minutes, the latency would still be 45 minutes, but a new car would then be finished every 15 minutes, instead of 20.
Under ideal circumstances, if all processing elements are synchronized and take the same amount of time to process, then each item can be received by each element just as it is released by the previous one, in a single clock cycle. That way, the items will flow through the pipeline at a constant speed, like waves in a water channel. In such "wave pipelines", no synchronization or buffering is needed between the stages, besides the storage needed for the data items.
More generally, buffering between the pipeline stages is necessary when the processing times are irregular, or when items may be created or destroyed along the pipeline. For example, in a graphics pipeline that processes triangles to be rendered on the screen, an element that checks the visibility of each triangle may discard the triangle if it is invisible, or may output two or more triangular pieces of the element if they are partly hidden. Buffering is also needed to accommodate irregularities in the rates at which the application feeds items to the first stage and consumes the output of the last one.
The buffer between two stages may be simply a hardware register with suitable synchronization and signalling logic between the two stages. When a stage A stores a data item in the register, it sends a "data available" signal to the next stage B. Once B has used that data, it responds with a "data received" signal to A. Stage A halts, waiting for this signal, before storing the next data item into the register. Stage B halts, waiting for the "data available" signal, if it is ready to process the next item but stage A has not provided it yet.
If the processing times of an element are variable, the whole pipeline may often have to stop, waiting for that element and all the previous ones to consume the items in their input buffers. The frequency of such pipeline stalls can be reduced by providing space for more than one item in the input buffer of that stage. Such a multiple-item buffer is usually implemented as a first-in, first-out queue. The upstream stage may still have to be halted when the queue gets full, but the frequency of those events will decrease as more buffer slots are provided. Queuing theory can tell the number of buffer slots needed, depending on the variability of the processing times and on the desired performance.
If some stage takes (or may take) much longer than the others, and cannot be sped up, the designer can provide two or more processing elements to carry out that task in parallel, with a single input buffer and a single output buffer. As each element finishes processing its current data item, it delivers it to the common output buffer, and takes the next data item from the common input buffer. This concept of "non-linear" or "dynamic" pipeline is exemplified by shops or banks that have two or more cashiers serving clients from a single waiting queue.
In some applications, the processing of an item Y by a stage A may depend on the results or effect of processing a previous item X by some later stage B of the pipeline. In that case, stage A cannot correctly process item Y until item X has cleared stage B.
This situation occurs very often in instruction pipelines. For example, suppose that Y is an arithmetic instruction that reads the contents of a register that was supposed to have been modified by an earlier instruction X. Let A be the stage that fetches the instruction operands, and B be the stage that writes the result to the specified register. If stage A tries to process instruction Y before instruction X reaches stage B, the register may still contain the old value, and the effect of Y would be incorrect.
In order to handle such conflicts correctly, the pipeline must be provided with extra circuitry or logic that detects them and takes the appropriate action. Strategies for doing so include:
A pipelined system typically requires more resources (circuit elements, processing units, computer memory, etc.) than one that executes one batch at a time, because its stages cannot share those resources, and because buffering and additional synchronization logic may be needed between the elements.
Moreover, the transfer of items between separate processing elements may increase the latency, especially for long pipelines.
The additional complexity cost of pipelining may be considerable if there are dependencies between the processing of different items, especially if a guess-and-backtrack strategy is used to handle them. Indeed, the cost of implementing that strategy for complex instruction sets has motivated some radical proposals to simplify computer architecture, such as RISC and VLIW. Compilers also have been burdened with the task of rearranging the machine instructions so as to improve the performance of instruction pipelines.
A central processing unit (CPU), also called a central processor or main processor, is the electronic circuitry within a computer that executes instructions that make up a computer program. The CPU performs basic arithmetic, logic, controlling, and input/output (I/O) operations specified by the instructions in the program. The computer industry used the term "central processing unit" as early as 1955. Traditionally, the term "CPU" refers to a processor, more specifically to its processing unit and control unit (CU), distinguishing these core elements of a computer from external components such as main memory and I/O circuitry.
The control unit (CU) is a component of a computer's central processing unit (CPU) that directs the operation of the processor. It tells the computer's memory, arithmetic and logic unit and input and output devices how to respond to the instructions that have been sent to the processor.
In computer science, 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 performed by different processor units with different parts of instructions processed in parallel.
Tomasulo’s algorithm is a computer architecture hardware algorithm for dynamic scheduling of instructions that allows out-of-order execution and enables more efficient use of multiple execution units. It was developed by Robert Tomasulo at IBM in 1967 and was first implemented in the IBM System/360 Model 91’s floating point unit.
In the domain of central processing unit (CPU) design, hazards are problems with the instruction pipeline in CPU microarchitectures when the next instruction cannot execute in the following clock cycle, and can potentially lead to incorrect computation results. Three common types of hazards are data hazards, structural hazards, and control hazards.
In the history of computer hardware, some early reduced instruction set computer central processing units used a very similar architectural solution, now called a classic RISC pipeline. Those CPUs were: MIPS, SPARC, Motorola 88000, and later the notional CPU DLX invented for education.
In computer architecture, register renaming is a technique that abstracts logical registers from physical registers. Every logical register has a set of physical registers associated with it. While a programmer in assembly language refers for instance to a logical register
accu, the processor transposes this name to one specific physical register on the fly. The physical registers are opaque and cannot be referenced directly but only via the canonical names.
In computer science, computer engineering and programming language implementations, a stack machine is a type of computer. In some cases, the term refers to a software scheme that simulates a stack machine.
The instruction cycle is the cycle that the central processing unit (CPU) follows from boot-up until the computer has shut down in order to process instructions. It is composed of three main stages: the fetch stage, the decode stage, and the execute stage.
Addressing modes are an aspect of the instruction set architecture in most central processing unit (CPU) designs. The various addressing modes that are defined in a given instruction set architecture define how the machine language instructions in that architecture identify the operand(s) of each instruction. An addressing mode specifies how to calculate the effective memory address of an operand by using information held in registers and/or constants contained within a machine instruction or elsewhere.
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In computer engineering, out-of-order execution is a paradigm used in most high-performance central processing units to make use of instruction cycles that would otherwise be wasted. In this paradigm, a processor executes instructions in an order governed by the availability of input data and execution units, rather than by their original order in a program. In doing so, the processor can avoid being idle while waiting for the preceding instruction to complete and can, in the meantime, process the next instructions that are able to run immediately and independently.
In software engineering, a pipeline consists of a chain of processing elements, arranged so that the output of each element is the input of the next; the name is by analogy to a physical pipeline. Usually some amount of buffering is provided between consecutive elements. The information that flows in these pipelines is often a stream of records, bytes, or bits, and the elements of a pipeline may be called filters; this is also called the pipes and filters design pattern. Connecting elements into a pipeline is analogous to function composition.
In computer engineering, microarchitecture, also called computer organization and sometimes abbreviated as µarch or uarch, is the way a given instruction set architecture (ISA) is implemented in a particular processor. A given ISA may be implemented with different microarchitectures; implementations may vary due to different goals of a given design or due to shifts in technology.
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In the design of pipelined computer processors, a pipeline stall is a delay in execution of an instruction in order to resolve a hazard.
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The Mill architecture is a novel belt machine-based computer architecture for general-purpose computing. It has been under development since about 2003 by Ivan Godard and his startup Mill Computing, Inc., formerly named Out Of The Box Computing, in East Palo Alto, California. Mill Computing claims it has a "10x single-thread power/performance gain over conventional out-of-order superscalar architectures" but "runs the same programs, without rewrite".
Latency oriented processor architecture is the microarchitecture of a microprocessor designed to serve a serial computing thread with a low latency. This is typical of most Central Processing Units (CPU) being developed since the 1970s. These architectures, in general, aim to execute as many instructions as possible belonging to a single serial thread, in a given window of time; however, the time to execute a single instruction completely from fetch to retire stages may vary from a few cycles to even a few hundred cycles in some cases. Latency oriented processor architectures are the opposite of throughput-oriented processors which concern themselves more with the total throughput of the system, rather than the service latencies for all individual threads that they work on.