Modules

Here is a list of all modules:

[detail level 1234]

NPP Core	Basic functions for library management, in particular library version and device property query functions
NPP Type Definitions and Constants
Basic NPP Data Types
NPP Image Processing
Arithmetic and Logical Operations	These functions can be found in the nppial library
Arithmetic Operations
AddC	Adds a constant value to each pixel of an image
MulC	Multiplies each pixel of an image by a constant value
MulCScale	Multiplies each pixel of an image by a constant value then scales the result by the maximum value for the data bit width
SubC	Subtracts a constant value from each pixel of an image
DivC	Divides each pixel of an image by a constant value
AbsDiffC	Determines absolute difference between each pixel of an image and a constant value
Add	Pixel by pixel addition of two images
AddSquare	Pixel by pixel addition of squared pixels from source image to floating point pixel values of destination image
AddProduct	Pixel by pixel addition of product of pixels from two source images to floating point pixel values of destination image
AddWeighted	Pixel by pixel addition of alpha weighted pixel values from a source image to floating point pixel values of destination image
Mul	Pixel by pixel multiply of two images
MulScale	Pixel by pixel multiplies each pixel of two images then scales the result by the maximum value for the data bit width
Sub	Pixel by pixel subtraction of two images
Div	Pixel by pixel division of two images
Div_Round	Pixel by pixel division of two images using result rounding modes
Abs	Absolute value of each pixel value in an image
AbsDiff	Pixel by pixel absolute difference between two images
Sqr	Square each pixel in an image
Sqrt	Pixel by pixel square root of each pixel in an image
Ln	Pixel by pixel natural logarithm of each pixel in an image
Exp	Exponential value of each pixel in an image
Logical Operations
AndC	Pixel by pixel logical and of an image with a constant
OrC	Pixel by pixel logical or of an image with a constant
XorC	Pixel by pixel logical exclusive or of an image with a constant
RShiftC	Pixel by pixel right shift of an image by a constant value
LShiftC	Pixel by pixel left shift of an image by a constant value
And	Pixel by pixel logical and of images
Or	Pixel by pixel logical or of images
Xor	Pixel by pixel logical exclusive or of images
Not	Pixel by pixel logical not of image
Alpha Composition
AlphaCompC	Composite two images using constant alpha values
AlphaPremulC	Premultiplies pixels of an image using a constant alpha value
AlphaComp	Composite two images using alpha opacity values contained in each image
AlphaPremul	Premultiplies image pixels by image alpha opacity values
Color and Sampling Conversion	Routines manipulating an image's color model and sampling format
Color Model Conversion	Routines for converting between various image color models
RGBToYUV	RGB to YUV color conversion
BGRToYUV	BGR to YUV color conversion
YUVToRGB	YUV to RGB color conversion
YUVToBGR	YUV to BGR color conversion
RGBToYUV422	RGB to YUV422 color conversion
YUV422ToRGB	YUV422 to RGB color conversion
RGBToYUV420	RGB to YUV420 color conversion
YUV420ToRGB	YUV420 to RGB color conversion
NV12ToRGB	NV12 to RGB color conversion
NV21ToRGB	NV21 to RGB color conversion
BGRToYUV420	BGR to YUV420 color conversion
YUV420ToBGR	YUV420 to BGR color conversion
NV12ToBGR	NV12 to BGR color conversion
NV21ToBGR	NV21 to BGR color conversion
RGBToYCbCr	RGB to YCbCr color conversion
YCbCrToRGB	YCbCr to RGB color conversion
YCbCrToBGR	YCbCr to BGR color conversion
YCbCrToBGR_709CSC	YCbCr to BGR_709CSC color conversion
RGBToYCbCr422	RGB to YCbCr422 color conversion
YCbCr422ToRGB	YCbCr422 to RGB color conversion
RGBToYCrCb422	RGB to YCrCb422 color conversion
YCrCb422ToRGB	YCrCb422 to RGB color conversion
BGRToYCbCr422	BGR to YCbCr422 color conversion
YCbCr422ToBGR	YCbCr422 to BGR color conversion
RGBToCbYCr422	RGB to CbYCr422 color conversion
CbYCr422ToRGB	CbYCr422 to RGB color conversion
BGRToCbYCr422	BGR to CbYCr422 color conversion
BGRToCbYCr422_709HDTV	BGR to CbYCr422_709HDTV color conversion
CbYCr422ToBGR	CbYCr422 to BGR color conversion
CbYCr422ToBGR_709HDTV	CbYCr422 to BGR_709HDTV color conversion
RGBToYCbCr420	RGB to YCbCr420 color conversion
YCbCr420ToRGB	YCbCr420 to RGB color conversion
RGBToYCrCb420	RGB to YCrCb420 color conversion
YCrCb420ToRGB	YCrCb420 to RGB color conversion
BGRToYCbCr420	BGR to YCbCr420 color conversion
BGRToYCbCr420_709CSC	BGR to YCbCr420_709CSC color conversion
BGRToYCbCr420_709HDTV	BGR to YCbCr420_709HDTV color conversion
BGRToYCrCb420_709CSC	BGR to YCrCb420_709CSC color conversion
YCbCr420ToBGR	YCbCr420 to BGR color conversion
YCbCr420ToBGR_709CSC	YCbCr420_709CSC to BGR color conversion
YCbCr420ToBGR_709HDTV	YCbCr420_709HDTV to BGR color conversion
BGRToYCrCb420	BGR to YCrCb420 color conversion
BGRToYCbCr411	BGR to YCbCr411 color conversion
RGBToYCbCr411	RGB to YCbCr411 color conversion
BGRToYCbCr	BGR to YCbCr color conversion
YCbCr411ToBGR	YCbCr411 to BGR color conversion
YCbCr411ToRGB	YCbCr411 to RGB color conversion
RGBToXYZ	RGB to XYZ color conversion
XYZToRGB	XYZ to RGB color conversion
RGBToLUV	RGB to LUV color conversion
LUVToRGB	LUV to RGB color conversion
BGRToLab	BGR to Lab color conversion
LabToBGR	Lab to BGR color conversion
RGBToYCC	RGB to PhotoYCC color conversion
YCCToRGB	PhotoYCC to RGB color conversion
RGBToHLS	RGB to HLS color conversion
HLSToRGB	HLS to RGB color conversion
BGRToHLS	BGR to HLS color conversion
HLSToBGR	HLS to BGR color conversion
RGBToHSV	RGB to HSV color conversion
HSVToRGB	HSV to RGB color conversion
JPEG Color Conversion
ColorToGray Conversion	Routines for converting color images to grayscale
ColorDebayer	Grayscale Color Filter Array to RGB Color Debayer conversion
Color Sampling Format Conversion	Routines for converting between various image color sampling formats
Color Gamma Correction	Routines for correcting image color gamma
Complement Color Key	Routines for performing complement color key replacement
Color Processing	Routines for performing image color manipulation
ColorTwist	Routines for converting between various image color models using user supplied matrix coefficients
ColorTwistBatch	Routines for converting between various image color models using user supplied matrix coefficients on batches of images
ColorLUT	Perform image color processing using members of various types of color look up tables
ColorLUTLinear	Perform image color processing using linear interpolation between members of various types of color look up tables
ColorLUTCubic	Perform image color processing using linear interpolation between members of various types of color look up tables
ColorLUTTrilinear	Perform image color processing using 3D trilinear interpolation between members of various types of color look up tables
ColorLUTPalette	Perform image color processing using various types of bit range restricted palette color look up tables
Compression	Image compression primitives
Quantization Functions
Data Exchange and Initialization	Functions for initializting, copying and converting image data
Image Set Operations	Functions for setting all pixels within the ROI to a specific value
Set	Functions for setting all pixels within the ROI to a specific value
Masked Set	The masked set primitives have an additional "mask image" input
Channel Set	The selected-channel set primitives set a single color channel in multi-channel images to a given value
Image Copy Operations	Functions for copying image pixels
Copy	Copy pixels from one image to another
Masked Copy	The masked copy primitives have an additional "mask image" input
Channel Copy	The channel copy primitives copy a single color channel from a multi-channel source image to any other color channel in a multi-channel destination image
Extract Channel Copy	The channel extract primitives copy a single color channel from a multi-channel source image to singl-channel destination image
Insert Channel Copy	The channel insert primitives copy a single-channel source image into one of the color channels in a multi-channel destination image
Packed To Planar Channel Copy	Split a packed multi-channel image into multiple single channel planes
Planar To Packed Channel Copy	Combine multiple image planes into a packed multi-channel image
Copy Constant Border	Methods for copying images and padding borders with a constant, user-specifiable color
Copy Replicate Border	Methods for copying images and padding borders with a replicates of the nearest source image pixel color
Copy Wrap Border	Methods for copying images and padding borders with wrapped replications of the source image pixel colors
Copy Sub-Pixel	Functions for copying linearly interpolated images using source image subpixel coordinates
Convert Bit Depth	Functions for converting bit depth without scaling
Convert To Increased Bit Depth	The integer conversion methods do not involve any scaling
Convert To Decreased Bit Depth	The integer conversion methods do not involve any scaling
Scale Bit Depth	Functions for scaling bit depth up or down
Scale To Higher Bit Depth	Functions for scaling images to higher bit depth
Scale To Lower Bit Depth	Functions for scaling images to lower bit depth
Duplicate Channel	Functions for duplicating a single channel image in a multiple channel image
Transpose	Functions for transposing images of various types
Swap Channels	Functions for swapping and duplicating channels in multiple channel images
Filtering Functions	Linear and non-linear image filtering functions
1D Linear Filter
FilterColumn	Apply convolution filter with user specified 1D column of weights
FilterColumnBorder	General purpose 1D convolution column filter with border control
FilterColumn32f	FilterColumn using floating-point weights
FilterColumnBorder32f	General purpose 1D column convolution filter using floating-point weights with border control
FilterRow	Apply convolution filter with user specified 1D row of weights
FilterRowBorder	General purpose 1D convolution row filter with border control
FilterRow32f	FilterRow using floating-point weights
FilterRowBorder32f	General purpose 1D row convolution filter using floating-point weights with border control
1D Window Sum
1D Window Column Sum	1D mask Window Column Sum for 8 and 16 bit images
1D Window Row Sum	1D mask Window Row Sum for 8 and 16 bit images
1D Window Sum with Border Control
1D Window Column Sum Border	1D mask Window Column Sum for 8 and 16 bit images with border control
1D Window Row Sum Border	1D mask Window Row Sum for 8 and 16 bit images with border control
Convolution
Filter	General purpose 2D convolution filter
Filter32f	General purpose 2D convolution filter using floating point weights
FilterBorder	General purpose 2D convolution filter with border control
FilterBorder32f	General purpose 2D convolution filter using floating-point weights with border control
2D Fixed Linear Filters
FilterBox	Computes the average pixel values of the pixels under a rectangular mask
FilterBoxBorder	Computes the average pixel values of the pixels under a rectangular mask with border control
FilterThresholdAdaptiveBoxBorder	Computes the average pixel values of the pixels under a square mask with border control
Rank Filters
FilterMax	Result pixel value is the maximum of pixel values under the rectangular mask region
FilterMaxBorder	Result pixel value is the maximum of pixel values under the rectangular mask region with border control
FilterMin	Result pixel value is the minimum of pixel values under the rectangular mask region
FilterMinBorder	Result pixel value is the minimum of pixel values under the rectangular mask region with border control
FilterMedian	Result pixel value is the median of pixel values under the rectangular mask region
Fixed Filters	Fixed filters perform linear filtering operations (such as convolutions) with predefined kernels of fixed sizes
FilterPrewitt	Filters the image using a Prewitt filter kernel
FilterPrewittBorder	Filters the image using a Prewitt filter kernel with border control
FilterScharr	Filters the image using a Scharr filter kernel
FilterScharrBorder	Filters the image using a Scharr filter kernel with border control
FilterSobel	Filters the image using a Sobel filter kernel
FilterSobelBorder	Filters the image using a Sobel filter kernel with border control
FilterRoberts	Filters the image using a Roberts filter kernel
FilterRobertsBorder	Filters the image using a Roberts filter kernel with border control
FilterLaplace	Filters the image using a Laplacian filter kernel
FilterLaplaceBorder	Filters the image using a Laplacian filter kernel with border control
FilterGauss	Filters the image using a Gaussian filter kernel
FilterGaussAdvanced	Filters the image using a separable Gaussian filter kernel with user supplied floating point coefficients:
FilterGaussBorder	Filters the image using a Gaussian filter kernel with border control
FilterGaussAdvancedBorder	Filters the image using a separable Gaussian filter kernel with user supplied floating point coefficients with border control
FilterGaussPyramidLayerDownBorder	Filters the image using a separable Gaussian filter kernel with user supplied floating point coefficients with downsampling and border control
FilterGaussPyramidLayerUpBorder	Filters the image using a separable Gaussian filter kernel with user supplied floating point coefficients with upsampling and border control
FilterBilateralGaussBorder	Filters the image using a bilateral Gaussian filter kernel with border control
FilterHighPass	Filters the image using a high-pass filter kernel
FilterHighPassBorder	Filters the image using a high-pass filter kernel with border control
FilterLowPass	Filters the image using a low-pass filter kernel
FilterLowPassBorder	Filters the image using a low-pass filter kernel with border control
FilterSharpen	Filters the image using a sharpening filter kernel:
FilterSharpenBorder	Filters the image using a sharpening filter kernel with border control
FilterUnsharpBorder	Filters the image using a unsharp-mask sharpening filter kernel with border control
FilterWienerBorder	Noise removal filtering of an image using an adaptive Wiener filter with border control
GradientVectorPrewittBorder	RGB Color to Prewitt Gradient Vector conversion using user selected fixed mask size and gradient distance method
GradientVectorScharrBorder	RGB Color to Scharr Gradient Vector conversion using user selected fixed mask size and gradient distance method
GradientVectorSobelBorder	RGB Color to Sobel Gradient Vector conversion using user selected fixed mask size and gradient distance method
Computer Vision
FilterCannyBorder	Performs Canny edge detection on a single channel 8-bit grayscale image and outputs a single channel 8-bit image consisting of 0x00 and 0xFF values with 0xFF representing edge pixels
FilterHarrisCornersBorder	Performs Harris Corner detection on a single channel 8-bit grayscale image and outputs a single channel 32-bit floating point image consisting the corner response at each pixel of the image
FilterHoughLine	Extracts Hough lines from a single channel 8-bit binarized (0, 255) source feature (canny edges, etc.) image
HistogramOfOrientedGradientsBorder	Performs Histogram Of Oriented Gradients operation on source image generating separate windows of Histogram Descriptors for each requested location
LabelMarkers	Generate image connected region label markers to be used for later image segmentation
CompressMarkerLabels	Removes sparseness between marker label IDs output from LabelMarkers call
BoundSegments	Adds boundary borders around connected regions using a border value of nBorderVal
Geometry Transforms	Routines manipulating an image geometry
ResizeSqrPixel	ResizeSqrPixel supports the following interpolation modes:
Resize	This simplified function replaces the previous version which was deprecated in an earlier release
ResizeBatch	In this function as in nppiResize the resize scale factor is automatically determined by the width and height ratios of oSrcRectROI and oDstRectROI
Remap	Remap supports the following interpolation modes:
Rotate	Rotates an image around the origin (0,0) and then shifts it
Rotate Utility Functions
Rotate
Mirror	Mirrors images horizontally, vertically or diagonally
MirrorBatch	Mirrors batches of images horizontally, vertically or diagonally
Affine Transforms
Affine Transform Utility Functions
Affine Transform	Transforms (warps) an image based on an affine transform
Affine Transform Batch	Details of the warp affine operation are described above in the WarpAffine section
Backwards Affine Transform	Transforms (warps) an image based on an affine transform
Quad-Based Affine Transform	Transforms (warps) an image based on an affine transform
Perspective Transform
Perspective Transform Utility Functions
Perspective Transform	Transforms (warps) an image based on a perspective transform
Perspective Transform Batch	Details of the warp perspective operation are described above in the WarpPerspective section
Backwards Perspective Transform	Transforms (warps) an image based on a perspective transform
Quad-Based Perspective Transform	Transforms (warps) an image based on an perspective transform
Linear Transforms	Linear image transformations
Fourier Transforms
Morphological Operations	Morphological image operations
Dilation	Dilation computes the output pixel as the maximum pixel value of the pixels under the mask
Dilation with border control	Dilation computes the output pixel as the maximum pixel value of the pixels under the mask
Dilate3x3	Dilation using a 3x3 mask with the anchor at its center pixel
Dilate3x3Border	Dilation using a 3x3 mask with the anchor at its center pixel with border control
Erode	Erosion computes the output pixel as the minimum pixel value of the pixels under the mask
Erosion with border control	Erosion computes the output pixel as the minimum pixel value of the pixels under the mask
Erode3x3	Erosion using a 3x3 mask with the anchor at its center pixel
Erode3x3Border	Erosion using a 3x3 mask with the anchor at its center pixel with border control
ComplexImageMorphology	Complex image morphological operations
MorphGetBufferSize	Before calling any of the MorphCloseBorder, MorphOpenBorder, MorphTopHatBorder, MorphBlackHatBorder, or MorphGradientBorder functions the application first needs to call the corresponding MorphGetBufferSize to determine the amount of device memory to allocate as a working buffer
MorphCloseBorder	Dilation followed by Erosion with border control
MorphOpenBorder	Erosion followed by Dilation with border control
MorphToHatBorder	Source pixel minus the morphological open pixel result with border control
MorphBlackHatBorder	Morphological close pixel result minus source pixel with border control
MorphGradientBorder	Morphological dilated pixel result minus morphological eroded pixel result with border control
Statistical Operations	Primitives for computing the statistical properties of an image
Sum	Primitives for computing the sum of all the pixel values in an image
Min	Primitives for computing the minimal pixel value of an image
MinIndx	Primitives for computing the minimal value and its indices (X and Y coordinates) of an image
Max	Primitives for computing the maximal pixel value of an image
MaxIndx	Primitives for computing the maximal value and its indices (X and Y coordinates) of an image
MinMax	Primitives for computing both the minimal and the maximal values of an image
MinMaxIndx	Primitives for computing the minimal and the maximal values with their indices (X and Y coordinates) of an image
Mean	Primitives for computing the arithmetic mean of all the pixel values in an image
Mean_StdDev	Primitives for computing both the arithmetic mean and the standard deviation of an image
Image Norms	Primitives for computing the norms of an image, the norms of difference, and the relative errors of two images
Norm_Inf	Primitives for computing the infinity norm of an image
Norm_L1	Primitives for computing the L1 norm of an image
Norm_L2	Primitives for computing the L2 norm of an image
NormDiff_Inf	Primitives for computing the infinity norm of difference of pixels between two images
NormDiff_L1	Primitives for computing the L1 norm of difference of pixels between two images
NormDiff_L2	Primitives for computing the L2 norm of difference of pixels between two images
NormRel_Inf	Primitives for computing the relative error of infinity norm between two images
NormRel_L1	Primitives for computing the relative error of L1 norm between two images
NormRel_L2	Primitives for computing the relative error of L2 norm between two images
DotProd	Primitives for computing the dot product of two images
CountInRange.	Primitives for computing the amount of pixels that fall into the specified intensity range
MaxEvery	Primitives for computing the maximal value of the pixel pair from two images
MinEvery	Primitives for computing the minimal value of the pixel pair from two images
Integral	Primitives for computing the integral image of a given image
SqrIntegral	Primitives for computing both the integral and the squared integral images of a given image
RectStdDev	Primitives for computing the stansdard deviation of the integral images
HistogramEven	Primitives for computing the histogram of an image with evenly distributed bins
HistogramRange	Primitives for computing the histogram of an image within specified ranges
Image Proximity	Primitives for computing the proximity measure between a source image and a template image
SqrDistanceFull_Norm	Primitives for computing the normalized Euclidean distance between two images with full mode
SqrDistanceSame_Norm	Primitives for computing the normalized Euclidean distance between two images with same mode
SqrDistanceValid_Norm	Primitives for computing the normalized Euclidean distance between two images with valid mode
CrossCorrFull_Norm	Primitives for computing the normalized cross correlation between two images with full mode
CrossCorrSame_Norm	Primitives for computing the normalized cross correlation between two images with same mode
CrossCorrValid_Norm	Primitives for computing the normalized cross correlation between two images with valid mode
CrossCorrValid	Primitives for computing the cross correlation between two images with valid mode
CrossCorrFull_NormLevel	Primitives for computing the normalized cross correlation coefficient between two images with full mode
CrossCorrSame_NormLevel	Primitives for computing the normalized cross correlation coefficient between two images with same mode
CrossCorrValid_NormLevel	Primitives for computing the normalized cross correlation coefficient between two images with valid mode
Image Quality Index	Primitives for computing the image quality index of two images
MaximumError	Primitives for computing the maximum error between two images
AverageError	Primitives for computing the average error between two images
MaximumRelativeError	Primitives for computing the maximum relative error between two images
AverageRelativeError	Primitives for computing the average relative error between two images
IQA	Primitives for computing the image quality between two images, such as MSE, PSNR, SSIM, and MS-SSIM
Memory Management	Routines for allocating and deallocating pitched image storage
Threshold and Compare Operations	Methods for pixel-wise threshold and compare operations
Thresholding Operations	Various types of image thresholding operations
Threshold Operations	Threshold image pixels
Threshold Greater Than Operations	Threshold greater than image pixels
Threshold Less Than Operations	Threshold less than image pixels
Threshold Value Operations	Replace thresholded image pixels with a value
Threshold Greater Than Value Operations	Replace image pixels greater than threshold with a value
Threshold Less Than Value Operations	Replace image pixels less than threshold with a value
Threshold Less Than Value Or Greater Than Value Operations	Replace image pixels less than thresholdLT or greater than thresholdGT with with valueLT or valueGT respectively
Comparison Operations	Compare the pixels of two images or one image and a constant value and create a binary result image
Compare Images Operations	Compare the pixels of two images and create a binary result image
Compare Image With Constant Operations	Compare the pixels of an image with a constant value and create a binary result image
Compare Image Differences With Epsilon Operations	Compare the pixels value differences of two images with an epsilon value and create a binary result image
Compare Image Difference With Constant Within Epsilon Operations	Compare differences between image pixels and constant within an epsilon value and create a binary result image
NPP Signal Processing
Arithmetic and Logical Operations
Arithmetic Operations
AddC	Adds a constant value to each sample of a signal
AddProductC	Adds product of a constant and each sample of a source signal to the each sample of destination signal
MulC	Multiplies each sample of a signal by a constant value
SubC	Subtracts a constant from each sample of a signal
SubCRev	Subtracts each sample of a signal from a constant
DivC	Divides each sample of a signal by a constant
DivCRev	Divides a constant by each sample of a signal
Add	Sample by sample addition of two signals
AddProduct	Adds sample by sample product of two signals to the destination signal
Mul	Sample by sample multiplication the samples of two signals
Sub	Sample by sample subtraction of the samples of two signals
Div	Sample by sample division of the samples of two signals
Div_Round	Sample by sample division of the samples of two signals with rounding
Abs	Absolute value of each sample of a signal
Sqr	Squares each sample of a signal
Sqrt	Square root of each sample of a signal
Cubrt	Cube root of each sample of a signal
Exp	E raised to the power of each sample of a signal
Ln	Natural logarithm of each sample of a signal
10Log10	Ten times the decimal logarithm of each sample of a signal
SumLn	Sums up the natural logarithm of each sample of a signal
Arctan	Inverse tangent of each sample of a signal
Normalize	Normalize each sample of a real or complex signal using offset and division operations
Cauchy, CauchyD, and CauchyDD2	Determine Cauchy robust error function and its first and second derivatives for each sample of a signal
Logical And Shift Operations
AndC	Bitwise AND of a constant and each sample of a signal
And	Sample by sample bitwise AND of samples from two signals
OrC	Bitwise OR of a constant and each sample of a signal
Or	Sample by sample bitwise OR of the samples from two signals
XorC	Bitwise XOR of a constant and each sample of a signal
Xor	Sample by sample bitwise XOR of the samples from two signals
Not	Bitwise NOT of each sample of a signal
LShiftC	Left shifts the bits of each sample of a signal by a constant amount
RShiftC	Right shifts the bits of each sample of a signal by a constant amount
Conversion Functions
Convert
Threshold
Filtering Functions	Functions that provide functionality of generating output signal based on the input signal like signal integral, etc
Integral	Compute the indefinite interal of a given signal
Initialization
Set
Zero
Copy
Statistical Functions	Functions that provide global signal statistics like: sum, mean, standard deviation, min, max, etc
MinEvery And MaxEvery Functions	Performs the min or max operation on the samples of a signal
Sum	Signal_min_every_or_max_every
Maximum
Minimum
Mean
Standard Deviation
Mean And Standard Deviation
Minimum_Maximum
Infinity Norm
L1 Norm
L2 Norm
Infinity Norm Diff
L1 Norm Diff
L2 Norm Diff
Dot Product
Count In Range
Count Zero Crossings
MaximumError	Primitives for computing the maximum error between two signals
AverageError	Primitives for computing the Average error between two signals
MaximumRelativeError	Primitives for computing the MaximumRelative error between two signals
AverageRelativeError	Primitives for computing the AverageRelative error between two signals
Memory Management
Malloc	Signal-allocator methods for allocating 1D arrays of data in device memory
Free	Free signal memory