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{{Short description|Use of a GPU for computations typically assigned to CPUs}}
 
{{About|the software that utalizes GPU hardware to run software that typically runs on CPUs|the GPU hardware specifically designed to run "general purpose" computing|General-purpose computing on graphics processing units (hardware)}}
<noinclude>{{Requested move notice|1=General-purpose computing on graphics processing units|2=Talk:General-purpose computing on graphics processing units (software)#Requested move 14 August 2025}}
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{{Merge|General-purpose computing on graphics processing units (hardware)|discuss=Talk:General-purpose computing on graphics processing units (hardware)#Proposed merge of General-purpose computing on graphics processing units (software) with General-purpose computing on graphics processing units (hardware)|date=August 2025}}
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{{More citations needed|date=February 2022}}
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===Vectorization===
{{See also|Vector_processor#GPU_vector_processing_features|SIMD|SWAR|Single instruction, multiple threads{{!}}SIMT}}
{{Unreferenced section|date=July 2017}}
Most operations on the GPU operate in a vectorized fashion: one operation can be performed on up to four values at once.{{Disputed inline|date=July 2025}} For example, if one color {{angbr|R1, G1, B1}} is to be modulated by another color {{angbr|R2, G2, B2}}, the GPU can produce the resulting color {{angbr|R1*R2, G1*G2, B1*B2}} in one operation. This functionality is useful in graphics because almost every basic data type is a vector (either 2-, 3-, or 4-dimensional).{{citation needed|date=July 2017}} Examples include vertices, colors, normal vectors, and texture coordinates.
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