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GPUArray—Wolfram Language Documentation

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• See Also
  • GPUArrayQ
  • ArrayQ
  • ArrayDepth
  • MatrixQ
  • VectorQ
  • Dimensions
  • NumericArray
  • SparseArray
  • Array
• Related Guides
  • GPU Computing
  • GPU Computing with NVIDIA
  • GPU Computing with Apple
  • GPU Programming

GPUArray[array]

yields an array stored in memory accessible for GPU-accelerated computation.

Create a GPUArray object from a vector:

Compute the cosine:

Converts to an ordinary list of values:

Test whether a GPUArray object is a vector:

A matrix:

Extract parts of a GPUArray object:

Get properties of a GPUArray object:

Dimensions:

Depth:

Byte count:

Apply arithmetic operations on GPUArray objects:

Addition:

Multiplication:

Power:

Evaluate numerically trigonometric functions:

Sine:

Cosine:

Arc cosine:

Compute transcendental functions:

Exp:

Log:

Power:

Evaluate efficiently hyperbolic functions:

Sinh:

Cosh:

Inverse cosine:

Evaluate numerically integer functions:

Ceiling:

Floor:

Round:

Compute absolute values and signs functions:

Abs:

Sign:

Absolute value of the real:

Find a discrete Fourier transform:

Inverse Fourier transform of a complex list:

Evaluate statistics functions on a GPUArray object:

Mean:

Geometric mean:

Variance:

Standard deviation:

Skewness:

Minimum of a GPUArray object:

Maximum:

Minimum and maximum:

Sort a GPUArray object:

Apply matrix operations on GPUArray objects:

Dot product:

Transpose:

Trace:

Solve a matrix-vector equation:

A matrix equation:

Solve a matrix-vector least-squares problem:

Solve a matrix-matrix least-squares problem:

Compute the singular value decomposition of a complex-valued matrix:

Up to expected precision loss, :

Switch to the GPU random number generator:

Random numbers are now generated using it:

Random integers:

Random complexes:

A specific seed will affect the current GPU random number generator:

Plot a list of values from a continuous probability distribution:

Plot an array of numbers:

Plot a matrix as an array of colors:

GPUArray autoevaluates if no supported GPUs were detected:

Operations without GPU-accelerated support fall back to CPU implementations:

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