The biggest difference between vector and scalar processors is how many data items each is handling at once. Computer processing is often a pretty complex science, and understanding how it works on a technical level frequently requires a lot of knowledge and expertise. When it comes to the basic processing types, though, it’s often easier to see things more simply. In essence, a vector processor aggregates multiple data points, processing each in turn. It’s often really good for complicated tasks that can be broken down into smaller jobs that will respond to a similar instruction. Vector processors are efficient when it comes to getting things done, but this efficiency can cause other parts of the computer system to go slowly. Scalar processors, on the other hand, typically handle just one job at a time, and work on what’s basically a point-to-point basis. This type of processor doesn’t usually impact the speed of the machine as a whole, but can be slower when it comes to finishing more complicated jobs. Both are important to many sectors, and some computers and devices actually use both simultaneously to maximize efficiency.
Broad Importance of Computer Processing
The part of a computer that allows it to function, at least on a very broad level, is generally known as the central processing unit (CPU). This unit carries out the instructions of various programs; it receives a program's instructions, decodes those instructions, and breaks them into individual parts. It then executes those instructions and reports the results, writing them back into the device’s temporary or permanent memory. Processors are usually formatted from the beginning as either vector or scalar.
Scalar processors are the most basic type of processor. These usually process just one item at a time, typically integers or floating point numbers. Floating point numbers are numbers that are either too large or small to be represented by integers. According to the scalar system of ordering information, each instruction is handled sequentially. As a result, scalar processing can take up some time.
How Vector Processors Work
In contrast, vector processors typically operate on an array of data points. This means that rather than handling each item individually, multiple items that all have the same instruction can be completed at once. This can save time over scalar processing, but also adds complexity to a system; this can and often does slow other functions. Vector processing usually works best when there is a large amount of data to be processed. In these instances, groups of data and individual data sets can be handled by one instruction.
Vector and scalar processors also differ in their startup times. A vector processor often requires a prolonged startup of the computer because of the multiple tasks being performed. Scalar processors, on the other hand, tend to start a computer in a much shorter amount of time since only single tasks are being executed.
Using the Two Together
Not all computer systems have to use one over the other, and in certain settings the two actually work in tandem. The superscalar processor is one example. This system takes elements of each type and combines them for even faster processing. Using instruction-level parallelism, superscalar processing can perform multiple operations at the same time. This allows for the CPU to perform at a much faster level than a basic scalar processor, without the additional complexity and other limitations of the vector system.
There can be problems with this type of processor, however, as it must determine which tasks can be performed in parallel and which are dependent on other tasks being completed first. Errors in data assignment often lead to crashes and other malfunctions.