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The basis behind array programming and thinking is to find and exploit the properties of data where individual elements are similar or adjacent. Unlike object orientation which implicitly breaks down data to its constituent parts (or scalar quantities), array orientation looks to group data and apply a uniform handling.
However, by definition, the addition of SIMD cannot, by itself, qualify a processor as an actual vector processor, because SIMD is fixed-length, and vectors are variable-length. The difference is illustrated below with examples, showing and comparing the three categories: Pure SIMD, Predicated SIMD, and Pure Vector Processing. [citation needed]
Basic Linear Algebra Subprograms (BLAS) is a specification that prescribes a set of low-level routines for performing common linear algebra operations such as vector addition, scalar multiplication, dot products, linear combinations, and matrix multiplication.
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Each instruction executed by a scalar processor typically manipulates one or two data items at a time. By contrast, each instruction executed by a vector processor operates simultaneously on many data items. An analogy is the difference between scalar and vector arithmetic. A superscalar processor is a mixture of the two.
A small team led by Igor Novikov started the project in 2003, based on the existing open source vector graphics editor Skencil. sK1 is a fork of the Skencil 0.6.x series which used Tk widgets for the user interface (this version had been dropped by the main Skencil developers who were working on a branch of the program based on GTK+).
A scalar processor is classified as a single instruction, single data processor in Flynn's taxonomy.The Intel 486 is an example of a scalar processor. It is to be contrasted with a vector processor where a single instruction operates simultaneously on multiple data items (and thus is referred to as a single instruction, multiple data processor). [2]
Another method of deriving vector and tensor derivative identities is to replace all occurrences of a vector in an algebraic identity by the del operator, provided that no variable occurs both inside and outside the scope of an operator or both inside the scope of one operator in a term and outside the scope of another operator in the same term ...