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Guidelines for Writing MATLAB Code to Generate Efficient HDL Code

MATLAB Design Requirements for HDL Code Generation

When you generate HDL code from your MATLAB® design, you are converting an algorithm into an architecture that must meet hardware area and speed requirements.

Your MATLAB design has the following requirements:

  • MATLAB code within the design must be supported for HDL code generation.

  • Inputs and outputs must not be matrices or structures.

If you are generating code from the command line, verify your code readiness for code generation with the following command:

If you use the HDL Workflow Advisor to generate code, this check runs automatically.

For a MATLAB language support reference, including supported functions from the Fixed-Point Designer™, see Functions Supported for HDL Code Generation.

Guidelines for Writing MATLAB code

For better HDL code and faster code generation, design your MATLAB code according to the following best practices:

  • Serialize your input and output data. Parallel data processing structures require more hardware resources and a higher pin count.

  • Use add and subtract algorithms instead of algorithms that use functions like sine, divide, and modulo. Add and subtract operations use fewer hardware resources.

  • Avoid large arrays and matrices. Large arrays and matrices require more registers and RAM for storage.

  • Convert your code from floating-point to fixed-point. Floating-point data types are inefficient for hardware realization. HDL Coder™ provides an automated workflow for floating-point to fixed-point conversion.

  • Unroll loops to increase speed at the cost of higher area; unroll fewer loops and enable the loop streaming optimization to conserve area at the cost of lower throughput.

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