GPU Acceleration

Run functions on a graphics processing unit (GPU)

To take advantage of the performance benefits offered by a modern graphics processing unit (GPU), certain Wavelet Toolbox™ functions support GPU arrays. This support requires Parallel Computing Toolbox™.


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cwtContinuous 1-D wavelet transform
cwtfilterbankContinuous wavelet transform filter bank
scaleSpectrumScale-averaged wavelet spectrum
timeSpectrumTime-averaged wavelet spectrum
wcoherenceWavelet coherence and cross-spectrum
wtContinuous wavelet transform with filter bank
wvdWigner-Ville distribution and smoothed pseudo Wigner-Ville distribution
dwtSingle-level 1-D discrete wavelet transform
dwt2Single-level discrete 2-D wavelet transform
dyaddownDyadic downsampling
dyadupDyadic upsampling
wavedec1-D wavelet decomposition
wavedec22-D wavelet decomposition
wextendExtend vector or matrix
fftFast Fourier transform
ifftInverse fast Fourier transform
fft22-D fast Fourier transform
ifft22-D inverse fast Fourier transform
fftshiftShift zero-frequency component to center of spectrum
ifftshiftInverse zero-frequency shift
convConvolution and polynomial multiplication
conv22-D convolution
filter1-D digital filter
filter22-D digital filter


Run MATLAB Functions on a GPU (Parallel Computing Toolbox)

Hundreds of functions in MATLAB® and other toolboxes run automatically on a GPU if you supply a gpuArray (Parallel Computing Toolbox) argument.

GPU Support by Release (Parallel Computing Toolbox)

Support for NVIDIA® GPU architectures by MATLAB release.

Featured Examples