answersLogoWhite

0


Best Answer

A very limited form of parallelism is achieved by using pipelining in that several instructions (up to the limit of the depth of the pipeline) are being processed (each at a different stage of instruction processing) at the same time. An example of this using a 6 stage pipeline is as follows:

  1. instruction completion (this is the oldest instruction stage)
  2. data storage to memory
  3. instruction execution & perform input/output
  4. data read from memory
  5. memory address resolution
  6. instruction fetch from memory (this is the newest instruction stage)
This form of parallelism was first used in the IBM 7030 Stretch computer released in 1961 but did not become a common feature in computer architectures until the introduction of RISC in the 1980s.

The main advantage of pipelining is that under normal conditions none of the instruction processing hardware becomes idle. The main disadvantage of pipelining is that unscheduled events (e.g. interrupts, branch mispredictions, arithmetic exceptions) cause pipeline content flushes and having to spend time reloading the now empty pipeline to resume correct processing.

Some computers designed with pipelines having an unusually high number of stages had their performance so degraded by that disadvantage that real world benchmarks showed their performance to be only slightly better than the traditional nonpipelined computers, even though their estimated performance was originally much higher. RISC specified that the number of stages in the pipeline should be kept to a minimum to reduce this problem.

User Avatar

Wiki User

7y ago
This answer is:
User Avatar

Add your answer:

Earn +20 pts
Q: How is parallel processing achieved using pipelining?
Write your answer...
Submit
Still have questions?
magnify glass
imp
Related questions

What has the author Frederic Oberti written?

Frederic Oberti has written: 'Image processing using parallel processing methods'


If a processor has begun executing an instruction before it completes the previous instruction it must be using?

pipelining


What has the author Raja Das written?

Raja Das has written: 'The design and implementation of a parallel unstructured Euler solver using software primitives' -- subject(s): Parallel processing, Computational grids


What has the author Abanindra N S Sarkar written?

Abanindra N. S. Sarkar has written: 'Image compression using parallel processing'


What can be achieved from the database using forms?

what can be achieved from the database using reports


Why you use parallel processing?

Parallel processing relies on several different computers hooked up so that each one actually only does a part of the processing (the math) so several different techniques or stages of development get done at the same time (close enuff) hence the name Parallel computers, they run in parallel, at the same time. 10 computers for one hour of computer processing then only takes one tenth of the time or 6 minutes. It may also be a single computer using number of processors undertaking similar processing simultaneously to complete the task in limited time. For example a radar tracker has one set of estimated or calculated parameters or fore casted parameters of expected target, other set of parameters is directly recorded from the target , advance correction is to be given for estimating next parameters hence parallel processing is vital to reduce the time of processing. Second example is getting hold of terrorists or criminals by using quick parallel processing using facilities like database banking ticketing reservations security entry records property and other such records of the gang . This may be a proposed solution requiring more research.


Define Distributed parallel processing?

First, let's define parallel processing. Parallel processing is a computing approach to increasing the rate at which a set of data is processed by processing different parts of the data at the same time. Distributed parallel processing is using parallel processing on multiple machines. One example of this is how some online communities (Folding@HOME, the Mersenne Prime search, etc.) allow users to sign up and dedicate their own computers to processing some data set given to them by the server. When thousands of users sign up for this, a lot of data can be processed in a very short amount of time. Another type of parallel computing which is (sometimes) called "distributed" is the idea of a cluster parallel computer. A cluster would be many CPUs hooked up via high-speed ethernet connections to a central hub (server) which gives each of them some work to do. This cluster method is similar to the method described in the above paragraph, except that all the CPUs are directly connected to the server, and their only purpose is to perform the calculations given to them.


In what career would you need to learn about parallel processing?

Computer programmers need to understand the technique of parallel processing. Often, when there is a large problem that needs to be solved, programmers initiate the use of more than one computer processor to work simultaneously on the problem. By using more than one processor, the speed in which the computer can work is increased dramatically and the problem is efficiently solved.


What is difference between parallel processing and vector processing?

Parallel processing Parallel processing is the simultaneous processing of the same task on two or moremicroprocessors in order to obtain faster results. The computer resources can include a single computer with multiple processors, or a number of computers connected by a network, or a combination of both. The processors access data through shared memory. Somesupercomputer parallel processing systems have hundreds of thousands of microprocessors.Vector processing"A vector processor, or array processor, is a CPU design wherein the instruction set includes operations that can perform mathematical operations on multiple data elements simultaneously. This is in contrast to a scalar processor, which handles one element at a time using multiple instructions. The vast majority of CPUs are scalar (or close to it). Vector processors were common in the scientific computing area, where they formed the basis of most supercomputers through the 1980s and into the 1990s, but general increases in performance and processor design saw the near-disappearance of the vector processor as a general-purpose CPU.


What is the hypothesis for parallel circuits?

Using a parallel circuit energy can be transferred through a parallel circuit.


Disadvantages transaction processing Disadvantages of transaction processing systems Advantages of using transaction processing system What are the advantages of transaction processing What ar?

disadvantages of transaction processing system


What is digital colour image processing?

It is the processing (changing) of color images using a computer.