Verify the Generated Code from Native Floating-Point

HDL Coder™ native floating-point technology can generate target-independent HDL code from your floating-point design. You can synthesize your floating-point design on any generic FPGA or ASIC. Floating-point designs have better precision, higher dynamic range, and a shorter development cycle than fixed-point designs. If your design has complex math and trigonometric operations, use native floating-point technology.

When representing infinitely real numbers with a finite number of bits, there can be rounding errors with the correct rounding range of values that the IEEE-754 standard specifies. To measure the rounding errors, you can specify the floating-point tolerance check based on relative error or ulp error. For more information about these rounding errors, see Relative Accuracy and ULP Considerations.

Specify the Tolerance Strategy

Before generating the testbench, specify the floating-point tolerance check for verifying the generated code.

To specify the tolerance check in the Configuration Parameters dialog box:

In the Apps tab, select HDL Coder. The HDL Code tab appears.
Click Settings. In the HDL Code Generation > Testbench pane, for Floating point tolerance check based on, specify relative error or ulp error.
Enter the Tolerance Value and click Apply. If you choose relative error, the default is a tolerance value of 1e-07. If you choose ulp error, the default tolerance value is zero. To learn more, see Numeric Considerations for Native Floating-Point.

To specify the tolerance strategy at the command-line, use:

Specify the floating point tolerance check setting by using FPToleranceStrategy.

% check for floating-point tolerance based on relative error 
hdlset_param('sfir_single', 'FPToleranceStrategy', 'Relative'); 

% check for floating-point tolerance based on the ULP error
hdlset_param('sfir_single', 'FPToleranceStrategy', 'ULP');

Based on the FPToleranceStrategy setting, enter the tolerance value by using FPToleranceValue.

 % if using relative error, enter custom tolerance value
hdlset_param('FP_test_16a', 'FPToleranceValue', 1e-06); 

% if using ULP error, enter tolerance value greater 
% than or equal to 1
hdlset_param('FP_test_16a', 'FPToleranceValue', 1);

Verify the Generated Code with HDL Test Bench

To generate an HDL test bench for verifying the generated code:

In the Configuration Parameters dialog box, on the HDL Code Generation > Test Bench pane, in the Test Bench Generation Output section, select HDL test bench.
In the Configuration section, make sure that Use file I/O to read/write test bench data is enabled. To generate a test bench that uses constants instead of file I/O, clear Use file I/O to read/write test bench data.
Click Apply, and then click Generate Test Bench.

To learn more about how HDL test bench generation works, see Test Bench Generation.

Verify the Generated Code with Cosimulation

To generate a cosimulation model for verifying the generated code:

In the Configuration Parameters dialog box, on the HDL Code Generation > Test Bench pane, for Cosimulation model for use with, select the cosimulation tool.
Click Apply, and then click Generate Test Bench.
After test bench generation, save the cosimulation model. In the model, double-click the Compare subsystem.
If you double-click the Assert_Out1 block, the block parameters show the Tolerance Value that you specify.
To look inside the Assert_Out1 block, click the mask. If you specify the floating-point tolerance check based on ulp error, the model shows a ULPChecker block.

The ULPChecker has a MATLAB Function block that shows how HDL Coder accounts for the ULP error when checking for numerical accuracy.
If you specify the floating-point tolerance check based on relative error, the model shows a RelErrCheck block.

RelerrCheck has a MATLAB Function block that shows how HDL Coder accounts for the relative error when checking for numerical accuracy.
In the Simulink^® Editor for the model, start simulation. At the end of cosimulation, check the compare: Out1 scope.
The scope compares the difference between the result signal from the cosimulation block and the reference signal from the DUT.