I/O Optimization

I/O improvements using frame-to-sample conversion, multiple sampling handling, and I/O thresholding

Optimize and reduce the I/O for algorithms that use large inputs in domains such as image processing, digital signal processing, and radar applications. To optimize the I/O needed for your design, use frame-to-sample conversion, multiple sampling handling, or I/O thresholding.

Functions

`hdl.npufun`	Apply neighborhood processing and element-wise operations to incoming image or matrix for frame-to-sample conversion (Since R2022b)
`hdl.iteratorfun`	Apply iterative operation to an incoming image or matrix for frame-to-sample conversion (Since R2022b)

Blocks

Neighborhood Processing Subsystem

Create algorithm that follows the neighborhood pattern (Since R2022b)

Topics

HDL Code Generation from Frame-Based Algorithms
Generate synthesizable HDL code from frame-based algorithms by using the HDL Coder™ frame-to-sample conversion to target sample-based and pixel-based hardware and reduce I/O consumption and prototyping times.
Optimize Area Usage for Frame-Based Algorithms with Tall Array Inputs
Generate area efficient HDL code from a frame-based algorithm that has input data with significantly more rows than columns.
Generate HDL Code from Frame-Based Models by Using Neighborhood Modeling Methods
Generate HDL code from frame-based models by using MATLAB Function blocks or the Neighborhood Processing Subsystem block.
Use Sample-Based Inputs and Frame-Based Inputs in an Algorithm
Generate HDL code from an algorithm that uses both sample-based and frame-based inputs.
Use Neighborhood, Reduction, and Iterator Patterns with a Frame-Based Model or Function for HDL Code Generation
Generate HDL code from a frame-based design that models neighborhood, reduction, and iterator patterns.

Featured Examples

Synthesize Code for Frame-Based Model

Generate HDL code for a Sobel edge detection frame algorithm and calculate the frames per second of your design by synthesizing the generated code with the Simulink® HDL Workflow Advisor.

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Offload Large Delays from Frame-Based Models to External Memory

Map large delays to external memory when generating an IP core from a frame-based algorithm.

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Generate IP Core for Frame-Based Model with AXI4 Stream Interfaces

Leverage the frame to sample optimization from HDL Coder™ to generate a sample-based IP core with AXI4-Stream interfaces from a frame-based Simulink® model. The generated IP core can then be deployed to hardware and verified using live streaming data from MATLAB®.

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Generate IP Core from Frame-Based Model with AXI4 Stream Video Interface

You can use the HDL Coder™ frame-to-sample optimization to design and deploy frame-based algorithms that use AXI4-Stream Video interfaces to enable high-speed video streaming.

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Compute Image Characteristics with a Frame-Based Model for HDL Code Generation

Use frame-based modeling to model an image processing algorithm to detect an object based on color.

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Convert Frame-Based Model to Fixed Point and Generate HDL Code

Use the Fixed-Point Tool to convert the data types in a frame-based model to fixed-point and generate HDL code using frame-to-sample conversion.

Generate HDL Code from Frame-Based Model by Using Neighborhood Processing with States

Generate HDL code for a frame-based model to convert Bayer pattern encoding to true color imaging.

Since R2024a
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