I/O 优化
优化并减少在图像处理、数字信号处理和雷达应用等领域使用大型输入的算法的 I/O。要优化设计所需的 I/O,请使用帧到采样的转换、多采样处理或 I/O 阈值。
函数
hdl.npufun | Apply neighborhood processing and element-wise operations to incoming image or matrix for frame-to-sample conversion (自 R2022b 起) |
hdl.iteratorfun | Apply iterative operation to an incoming image or matrix for frame-to-sample conversion (自 R2022b 起) |
模块
| Neighborhood Processing Subsystem | Create algorithm that follows the neighborhood pattern (自 R2022b 起) |
主题
- 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.






