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What is the Difference Between Vector and Array Processing?

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Vector and array processing are essentially the same because, with slight and rare differences, a vector processor and an array processor are the same type of processor. A processor, or central processing unit (CPU), is a computer chip that handles most of the information and functions processed through a computer. A vector processor is in contrast to the simpler scalar processor, which handles only one piece of information at a time.

In discussions about vector and array processing, the two terms are used interchangeably, but they are technically slightly different. An array is made up of indexed collections of information called indices, the plural form of the word "index." Though an array can, in rare cases, have only one index collection, a vector is technically indicative of an array with at least two indices. Vectors are sometimes referred to as "blocks" of computer data.

Vector and array processing technology is not usually used in home or office computers. This technology is most often seen in high-traffic servers. Servers are racks of storage drives designed to house and allow access to information from several different users at different computers located on a computer network.

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Scalar processing technology operates on different principles than vector and array processing technology and is the most common type of processing hardware used in the average computer. A superscalar processor is a processor that operates like a scalar processor, but it has many different units within the CPU which each handle and process data simultaneously. The higher-performance superscalar processor type is also equipped with programming that makes it efficiently assign data processing to the available scalar units within the CPU. Most modern home computer processors are superscalar.

Inside a computer, a processor looks like a little shiny square about the size of a portable moist towelette wrapper, seated in a plastic part called a socket. The socket is embedded in the motherboard or mainboard chip on a computer, and locks the processor into place. It is usually underneath a cooling hardware part called a heatsink assembly, a mostly metal device that can include a fan, which can be found attached to the motherboard using a sturdy clip and bracket. Each type of processor has its own socket type compatibility, so a processor that does vector and array processing would definitely not be compatible with a scalar processor socket. A vector-type processor would probably not fit into the processor socket of another vector processor, even if it was made by the same manufacturer.

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MrMoody
Post 4

@Mammmood - The only exception to that would be if you strung out a bunch of computers together. When I was in college I heard of massively parallel computing, where hundreds or thousands of independent computers were connected, all working on various problems. In such a scenario you would beat out the scalar processing I would think.

Mammmood
Post 3

@SkyWhisperer - I think the vector processor would always win out, all other things being equal. If I understand correctly, the vector processor basically computes the data in chunks, or blocks as the article calls them.

If these vectors have two indices, then they are like a matrix of some sort. Imagine a filing cabinet with two columns of cabinets (corresponding to the two indices of the array) along with however many rows of cabinets that it has.

You can put more information into that whole cabinet than you can with one standalone cabinet drawer somewhere else. I think this kind of chunk processing will always be faster.

SkyWhisperer
Post 2

I know a little bit about vectors from my work in vector graphics. In vector graphics, the computers draw the images on the screen using mathematical formulas, rather than storing individual pixels in the images.

I assume that it’s similar with vector or array processing; arrays store the data, rather than individual units. Clearly, arrays are better, although I am sure array size would affect performance.

What I wonder is how the processing speed of a vector processor would compare with that of the biggest superscalar processor?

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