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The company is also working to design another generation of its traditional systems - known as vector processors.
In fact, vector processors work best only when there are large amounts of data to be worked on.
But to a vector processor, this task looks considerably different:
Most supercomputers of the era took another approach to higher performance, using a single very high speed vector processor.
It was one of the first machines to use a vector processor to improve performance on appropriate scientific applications.
The vector processor approach evolved into the pipeline architecture used in most processors today.
Vector processors take this concept one step further.
But more than that, a vector processor may have multiple functional units adding those numbers in parallel.
In a vector processor, by contrast, a single instruction operates simultaneously on multiple data items.
By the 1980s, many supercomputers used parallel vector processors.
Vector processors use this technique with one additional "trick".
A specialized vector processor can line up hundreds of thousands of calculations and then race through them.
Almost all vector processors use the load/store approach.
The new systems use software to solve problems that once required the processing power of traditional supercomputers, which are known as vector processors.
Each node had 4 vector processors, giving a total of 112 processors.
In the 1960s pipelining was viewed as an innovation, and by the 1970s the use of vector processors had been well established.
A vector processor executes the same operation on multiple pieces of data at the same time.
As the name implies, vector processors deal with multiple pieces of data in the context of one instruction.
Processors, especially vector processors, are often optimized for array operations.
Applications must be specially coded to take advantage of the vector processor, which allows them to perform certain mathematical operations very quickly.
Some processors also include vector processor capability.
The T3D machines are intended to establish a middle ground between the vector processors and the massively parallel systems.
"Vector processors have high-level operations that work on linear arrays of numbers or vectors.
Vector processors can greatly improve performance on certain workloads, notably numerical simulation and similar tasks.
Due to the highly parallel nature of vector processors, these processors have had a huge impact in specific data processing applications.