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Implement Control Signals Based Mathematical Functions using HDL Coder

This document gives the overview of the control signal based fixed point mathematical functions in HDLMathLib and examples associated with all the blocks present in the HDLMathLib by using HDL Coder™. HDLMathLib includes following blocks with control ports.

  1. Sqrt

  2. Atan2

  3. Sin

  4. Cos

  5. SinCos

  6. Cos+jSin

  7. Reciprocal

  8. Divide

HDLMathLib Library With Control Ports for Mathematical Functions

To see all the mathematical function blocks in the HDLMathLib library, open the library using following command.

open_system('HDLMathLib')

You can see various mathematical function blocks with control ports. Sqrt, Atan2, SinCos, Reciprocal and Divide blocks are described with example in the following sections. You can use sin, cos, Cos+jsin blocks in your model same way by referring below sections.

Sqrt Block with Control Signals

Each port of the Sqrt block is as explained below.

When you open the Sqrt block, it uses MATLAB Function blocks for the data and valid lines. This is as shown below.

open_system('hdlcoder_sqrt_bitset_control')
open_system('hdlcoder_sqrt_bitset_control/Sqrt')

Example using Contol Signals based Sqrt Block

This section shows how to implement an example using control signal based Square root block and generate HDL code by using HDL Coder™.

Open and Run Simulink Model

Before opening the model, set the input as follows. You can chose to set different input as per your requirement. This example uses following inputs which is linear.

SQRT_input = fi(1/2^17:1/2^17:1,0,18,17)';

Specify the wordlength for fixed-point datatypes and the pipeline latency for the model. Go through the documentation for latency calculation.

WL = 18;  latency = 20;

Open the model hdlcoder_sqrt_bitset_control and specify sufficient stop time that required to process all the input combinations.

stoptime = length(SQRT_input)-1+latency;
open_system('hdlcoder_sqrt_bitset_control')
sim('hdlcoder_sqrt_bitset_control')

You can see the below waveform when you simulate the above model. You can see that dataOut is valid when validOut is high.

Validate Simulink Output by Using Reference Output

To validate the output obtained by simulating the Simulink model, you can compare the Simulink output with a reference output. To obtain the reference output, use the sqrt function.

Compute the reference output by using the sqrt function.

ref_SQRT = sqrt(double(SQRT_input));

Use logical indexing to extract valid output.

implementation_SQRT = simulink_SQRT(valid_output);

To validate the output, plot the comparison results by using the comparison_plot function in this example. You can see that the maximum error observed from the comparison results is quite small.

comparison_plot_sqrt(ref_SQRT,implementation_SQRT,1,'SQRT linear input');
Maximum Error SQRT linear input 3.814697e-06 
Maximum PctError SQRT linear input 3.803159e-02 

Generate HDL Code for Square Root Implementation

Before you generate code, you can see the HDL settings saved on the model by using the hdlsaveparams function.

hdlsaveparams('hdlcoder_sqrt_bitset_control')
%% Set Model 'hdlcoder_sqrt_bitset_control' HDL parameters
hdlset_param('hdlcoder_sqrt_bitset_control', 'Backannotation', 'on');
hdlset_param('hdlcoder_sqrt_bitset_control', 'HDLSubsystem', 'hdlcoder_sqrt_bitset_control/Sqrt');
hdlset_param('hdlcoder_sqrt_bitset_control', 'ResetType', 'Synchronous');
hdlset_param('hdlcoder_sqrt_bitset_control', 'ResourceReport', 'on');
hdlset_param('hdlcoder_sqrt_bitset_control', 'SynthesisTool', 'Xilinx Vivado');
hdlset_param('hdlcoder_sqrt_bitset_control', 'SynthesisToolChipFamily', 'Virtex7');
hdlset_param('hdlcoder_sqrt_bitset_control', 'SynthesisToolDeviceName', 'xc7v2000t');
hdlset_param('hdlcoder_sqrt_bitset_control', 'SynthesisToolPackageName', 'fhg1761');
hdlset_param('hdlcoder_sqrt_bitset_control', 'SynthesisToolSpeedValue', '-2');
hdlset_param('hdlcoder_sqrt_bitset_control', 'TargetDirectory', 'hdl_prj\hdlsrc');
hdlset_param('hdlcoder_sqrt_bitset_control', 'TargetFrequency', 500);
hdlset_param('hdlcoder_sqrt_bitset_control', 'Traceability', 'on');

% Set SubSystem HDL parameters
hdlset_param('hdlcoder_sqrt_bitset_control/Sqrt', 'FlattenHierarchy', 'on');

hdlset_param('hdlcoder_sqrt_bitset_control/Sqrt/LumpLatency', 'Architecture', 'MATLAB Datapath');
% Set SubSystem HDL parameters
hdlset_param('hdlcoder_sqrt_bitset_control/Sqrt/LumpLatency', 'FlattenHierarchy', 'on');

hdlset_param('hdlcoder_sqrt_bitset_control/Sqrt/ValidLine', 'Architecture', 'MATLAB Datapath');
% Set SubSystem HDL parameters
hdlset_param('hdlcoder_sqrt_bitset_control/Sqrt/ValidLine', 'FlattenHierarchy', 'on');

To generate HDL code for the Sqrt block in the model, use the makehdl function.

  makehdl('hdlcoder_sqrt_bitset_control/Sqrt')
  close_system('hdlcoder_sqrt_bitset_control')
  close all;
### Generating HDL for 'hdlcoder_sqrt_bitset_control/Sqrt'.
### Using the config set for model <a href="matlab:configset.showParameterGroup('hdlcoder_sqrt_bitset_control', { 'HDL Code Generation' } )">hdlcoder_sqrt_bitset_control</a> for HDL code generation parameters.
### Running HDL checks on the model 'hdlcoder_sqrt_bitset_control'.
### Begin compilation of the model 'hdlcoder_sqrt_bitset_control'...
### Applying HDL optimizations on the model 'hdlcoder_sqrt_bitset_control'...
### <a href="matlab:configset.internal.open('hdlcoder_sqrt_bitset_control','AdaptivePipelining')">'AdaptivePipelining'</a> is set to 'Off' for the model. 'AdaptivePipelining' can improve the achievable clock frequency and reduce the area usage on FPGA boards. To enable adaptive pipelining, set the option to 'On'. When adaptive pipelining is enabled, it inserts pipeline registers to create patterns that efficiently map blocks to DSP units on the target FPGA device.
### <a href="matlab:configset.internal.open('hdlcoder_sqrt_bitset_control','LUTMapToRAM')">'LUTMapToRAM'</a> is set to 'On' for the model. This option is used to map lookup tables to a block RAM in hardware.  To disable pipeline insertion for mapping lookup tables to RAM, set the option to 'Off'.
### Begin model generation.
### Model generation complete.
### Begin VHDL Code Generation for 'hdlcoder_sqrt_bitset_control'.
### Working on hdlcoder_sqrt_bitset_control/Sqrt/Sqrt as hdl_prj/hdlsrc/hdlcoder_sqrt_bitset_control/Sqrt_block.vhd.
### Working on hdlcoder_sqrt_bitset_control/Sqrt as hdl_prj/hdlsrc/hdlcoder_sqrt_bitset_control/Sqrt.vhd.
### Generating package file hdl_prj/hdlsrc/hdlcoder_sqrt_bitset_control/Sqrt_pkg.vhd.
### Code Generation for 'hdlcoder_sqrt_bitset_control' completed.
### Generating HTML files for code generation report at <a href="matlab:web('/tmp/Bdoc21b_1757077_221275/tpcf1538dd/hdl_prj/hdlsrc/hdlcoder_sqrt_bitset_control/html/hdlcoder_sqrt_bitset_control_codegen_rpt.html');">hdlcoder_sqrt_bitset_control_codegen_rpt.html</a>
### Creating HDL Code Generation Check Report file:///tmp/Bdoc21b_1757077_221275/tpcf1538dd/hdl_prj/hdlsrc/hdlcoder_sqrt_bitset_control/Sqrt_report.html
### HDL check for 'hdlcoder_sqrt_bitset_control' complete with 0 errors, 0 warnings, and 2 messages.
### HDL code generation complete.

Sqrt Block Synthesis Performance

Following digrams shows the Sqrt block synthesis performance on the Xilinx Virtex 7 and intel Stratix V devices.

Atan2 Block with Control Signals

Each port of the Atan2 block is as explained below.

The Atan2 block has number of iterations as mask parameter. The default value is 11 and latency depends on this masked parameter.

When you open the Atan2 block, it uses MATLAB Function blocks for the data and valid lines. This is as shown below.

open_system('hdlcoder_atan2_control')
open_system('hdlcoder_atan2_control/Atan2')
open_system('hdlcoder_atan2_control/Atan2','force')

Example using Control Signal based Atan2 Block

This section shows how to implement an example using control signal based Atan2 block and generate HDL code by using HDL Coder™.

Open and Run Simulink Model

Before opening the model, set the input as follows. You can chose to set different input as per your requirement. This example uses following inputs which is linear and sweep through input values -pi to pi.

input_values = (-pi:.01/(2*pi):pi)';
RADIUS = 10.^(-2.5:.25:0);

Specify the wordlength for fixed-point datatypes and the pipeline latency for the model. Go through the documentation for latency calculation. The latency depends up on the number of iterations.

WL_atan2 = 18; latency_atan2 = 14;

Setup variables for logging input x and y values.

x_log = zeros(length(input_values)*length(RADIUS),1);
y_log = zeros(length(input_values)*length(RADIUS),1);
for outerindex = 0:length(RADIUS)-1
    for index = 1:length(input_values)
        input = input_values(index);  % access current value
        y = RADIUS(outerindex+1)*sin(input);               % compute y
        x = RADIUS(outerindex+1)*cos(input);               % compute x
        addr = outerindex*length(input_values)+index;
        y_log(addr) = y;
        x_log(addr) = x;
    end
end

Open the model hdlcoder_atan2_control and specify sufficient stop time that required to process all the input combinations. The model has Atan2 block that implements the Atan2 using CORDIC algorithm for a validIn control signal.

stoptime_atan2 = length(x_log)-1+latency_atan2;
close all
open_system('hdlcoder_atan2_control')
sim('hdlcoder_atan2_control')

You can see the below waveform when you simulate the above model. You can see that dataOut is valid when validOut is high.

Validate Simulink Output By Using Reference Output

To validate the output obtained by simulating the Simulink model, you can compare the Simulink output with a reference output. To obtain the reference output, use the atan2 MATLAB function.

Compute the reference output by using the atan2 function. You can see that the maximum error observed from the comparison results is quite small.

comparison_plot_atan2(atan2(y_log,x_log),sim_final_theta(valid_out),3,'theta');
Maximum Error theta 7.233221e-03 

Generate HDL Code for Atan2 Implementation

Before you generate code, you can see the HDL settings saved on the model by using the hdlsaveparams function.

hdlsaveparams('hdlcoder_atan2_control')
%% Set Model 'hdlcoder_atan2_control' HDL parameters
hdlset_param('hdlcoder_atan2_control', 'HDLSubsystem', 'hdlcoder_atan2_control/Atan2');
hdlset_param('hdlcoder_atan2_control', 'ResetType', 'Synchronous');
hdlset_param('hdlcoder_atan2_control', 'SynthesisTool', 'Xilinx Vivado');
hdlset_param('hdlcoder_atan2_control', 'SynthesisToolChipFamily', 'Virtex7');
hdlset_param('hdlcoder_atan2_control', 'SynthesisToolDeviceName', 'xc7v2000t');
hdlset_param('hdlcoder_atan2_control', 'SynthesisToolPackageName', 'fhg1761');
hdlset_param('hdlcoder_atan2_control', 'SynthesisToolSpeedValue', '-2');
hdlset_param('hdlcoder_atan2_control', 'TargetDirectory', 'hdl_prj\hdlsrc');
hdlset_param('hdlcoder_atan2_control', 'TargetFrequency', 500);

hdlset_param('hdlcoder_atan2_control/Atan2/LumpLatency', 'Architecture', 'MATLAB Datapath');
% Set SubSystem HDL parameters
hdlset_param('hdlcoder_atan2_control/Atan2/LumpLatency', 'FlattenHierarchy', 'on');

hdlset_param('hdlcoder_atan2_control/Atan2/ValidLine', 'Architecture', 'MATLAB Datapath');
% Set SubSystem HDL parameters
hdlset_param('hdlcoder_atan2_control/Atan2/ValidLine', 'FlattenHierarchy', 'on');

To generate HDL code for the Atan2 block in the model, use the makehdl function.

makehdl('hdlcoder_atan2_control/Atan2')
close_system('hdlcoder_atan2_control')
close all;
### Generating HDL for 'hdlcoder_atan2_control/Atan2'.
### Using the config set for model <a href="matlab:configset.showParameterGroup('hdlcoder_atan2_control', { 'HDL Code Generation' } )">hdlcoder_atan2_control</a> for HDL code generation parameters.
### Running HDL checks on the model 'hdlcoder_atan2_control'.
### Begin compilation of the model 'hdlcoder_atan2_control'...
### Applying HDL optimizations on the model 'hdlcoder_atan2_control'...
### <a href="matlab:configset.internal.open('hdlcoder_atan2_control','AdaptivePipelining')">'AdaptivePipelining'</a> is set to 'Off' for the model. 'AdaptivePipelining' can improve the achievable clock frequency and reduce the area usage on FPGA boards. To enable adaptive pipelining, set the option to 'On'. When adaptive pipelining is enabled, it inserts pipeline registers to create patterns that efficiently map blocks to DSP units on the target FPGA device.
### <a href="matlab:configset.internal.open('hdlcoder_atan2_control','LUTMapToRAM')">'LUTMapToRAM'</a> is set to 'On' for the model. This option is used to map lookup tables to a block RAM in hardware.  To disable pipeline insertion for mapping lookup tables to RAM, set the option to 'Off'.
### Begin model generation.
### Model generation complete.
### Begin VHDL Code Generation for 'hdlcoder_atan2_control'.
### Working on hdlcoder_atan2_control/Atan2/Enabled Subsystem as hdl_prj/hdlsrc/hdlcoder_atan2_control/Enabled_Subsystem.vhd.
### Working on hdlcoder_atan2_control/Atan2/Atan2 as hdl_prj/hdlsrc/hdlcoder_atan2_control/Atan2_block.vhd.
### Working on hdlcoder_atan2_control/Atan2 as hdl_prj/hdlsrc/hdlcoder_atan2_control/Atan2.vhd.
### Code Generation for 'hdlcoder_atan2_control' completed.
### Creating HDL Code Generation Check Report file:///tmp/Bdoc21b_1757077_221275/tpcf1538dd/hdl_prj/hdlsrc/hdlcoder_atan2_control/Atan2_report.html
### HDL check for 'hdlcoder_atan2_control' complete with 0 errors, 0 warnings, and 2 messages.
### HDL code generation complete.

Atan2 Block Synthesis Performance

Following digrams shows the Atan2 block synthesis performance on the Xilinx Virtex 7 and intel Stratix V devices.

SinCos Block with Control Signals

Each port of the SinCos block is as explained below.

The SinCos block has number of iterations as the mask parameter.The default value is 11 and latency depends on this masked parameter.

When you open the SinCos block, it uses MATLAB Function blocks for the data and valid lines. This is as shown below.

open_system('hdlcoder_sincos_control')
open_system('hdlcoder_sincos_control/SinCos')
open_system('hdlcoder_sincos_control/SinCos','force')

Example using Control Signal based SinCos Block

This section shows how to implement an example using control signal based SinCos block and generate HDL code by using HDL Coder™.

Open and Run Simulink Model

Before opening the model, set the input as follows. You can chose to set different input as per your requirement. This example uses following inputs which is linear and sweep through input values -pi to pi.

input_values = (-pi:.01/(2*pi):pi)';

Specify the wordlength for fixed-point datatypes and the pipeline latency for the model. Go through the documentation for latency calculation. The latency depends up on the number of iterations

WL_SinCos = 18; latency_SinCos = 12;

Open the model hdlcoder_sincos_control and specify sufficient stop time that required to process all the input combinations. The model has SinCos block that implements the SinCos using CORDIC algorithm for a validIn control signal. The remaining trigonometric function blocks(Sin, Cos and Cos + jSin) use the same CORDIC approximation method and the interface ports differs respectively.

stoptime_sincos = length(input_values)-1+latency_SinCos;
open_system('hdlcoder_sincos_control')
sim('hdlcoder_sincos_control')

You can see the below waveform when you simulate the above model. You can see that dataOut is valid when validOut is high.

Validate Simulink Output By Using Reference Output

To validate the output obtained by simulating the Simulink model, you can compare the Simulink output with a reference output. To obtain the reference output, use the sin and cos MATLAB function.

Compute the reference output by using the sin function. You can see that the maximum error observed from the comparison results is quite small.

comparison_plot_sincos(sin(input_values),sim_final_sintheta(valid_out),5,'sin');
Maximum Error sin 1.005291e-03 

Compute the reference output by using the Cos function. You can see that the maximum error observed from the comparison results is quite small.

comparison_plot_sincos(cos(input_values),sim_final_costheta(valid_out),6,'cos');
Maximum Error cos 1.008159e-03 

Generate HDL Code for SinCos Implementation

Before you generate code, you can see the HDL settings saved on the model by using the hdlsaveparams function.

hdlsaveparams('hdlcoder_sincos_control')
%% Set Model 'hdlcoder_sincos_control' HDL parameters
hdlset_param('hdlcoder_sincos_control', 'HDLSubsystem', 'hdlcoder_sincos_control/SinCos');
hdlset_param('hdlcoder_sincos_control', 'ResetType', 'Synchronous');
hdlset_param('hdlcoder_sincos_control', 'SynthesisTool', 'Xilinx Vivado');
hdlset_param('hdlcoder_sincos_control', 'SynthesisToolChipFamily', 'Virtex7');
hdlset_param('hdlcoder_sincos_control', 'SynthesisToolDeviceName', 'xc7v2000t');
hdlset_param('hdlcoder_sincos_control', 'SynthesisToolPackageName', 'fhg1761');
hdlset_param('hdlcoder_sincos_control', 'SynthesisToolSpeedValue', '-2');
hdlset_param('hdlcoder_sincos_control', 'TargetDirectory', 'hdl_prj\hdlsrc');
hdlset_param('hdlcoder_sincos_control', 'TargetFrequency', 500);

hdlset_param('hdlcoder_sincos_control/SinCos/LumpLatency', 'Architecture', 'MATLAB Datapath');
% Set SubSystem HDL parameters
hdlset_param('hdlcoder_sincos_control/SinCos/LumpLatency', 'FlattenHierarchy', 'on');

hdlset_param('hdlcoder_sincos_control/SinCos/LumpLatency1', 'Architecture', 'MATLAB Datapath');
% Set SubSystem HDL parameters
hdlset_param('hdlcoder_sincos_control/SinCos/LumpLatency1', 'FlattenHierarchy', 'on');

hdlset_param('hdlcoder_sincos_control/SinCos/ValidLine', 'Architecture', 'MATLAB Datapath');
% Set SubSystem HDL parameters
hdlset_param('hdlcoder_sincos_control/SinCos/ValidLine', 'FlattenHierarchy', 'on');

To generate HDL code for the SinCos block in the model, use the makehdl function.

makehdl('hdlcoder_sincos_control/SinCos')
close_system('hdlcoder_sincos_control')
close all;
### Generating HDL for 'hdlcoder_sincos_control/SinCos'.
### Using the config set for model <a href="matlab:configset.showParameterGroup('hdlcoder_sincos_control', { 'HDL Code Generation' } )">hdlcoder_sincos_control</a> for HDL code generation parameters.
### Running HDL checks on the model 'hdlcoder_sincos_control'.
### Begin compilation of the model 'hdlcoder_sincos_control'...
### Applying HDL optimizations on the model 'hdlcoder_sincos_control'...
### <a href="matlab:configset.internal.open('hdlcoder_sincos_control','AdaptivePipelining')">'AdaptivePipelining'</a> is set to 'Off' for the model. 'AdaptivePipelining' can improve the achievable clock frequency and reduce the area usage on FPGA boards. To enable adaptive pipelining, set the option to 'On'. When adaptive pipelining is enabled, it inserts pipeline registers to create patterns that efficiently map blocks to DSP units on the target FPGA device.
### <a href="matlab:configset.internal.open('hdlcoder_sincos_control','LUTMapToRAM')">'LUTMapToRAM'</a> is set to 'On' for the model. This option is used to map lookup tables to a block RAM in hardware.  To disable pipeline insertion for mapping lookup tables to RAM, set the option to 'Off'.
### Begin model generation.
### Model generation complete.
### Begin VHDL Code Generation for 'hdlcoder_sincos_control'.
### Working on hdlcoder_sincos_control/SinCos/Enabled Subsystem as hdl_prj/hdlsrc/hdlcoder_sincos_control/Enabled_Subsystem.vhd.
### Working on hdlcoder_sincos_control/SinCos/SinCos as hdl_prj/hdlsrc/hdlcoder_sincos_control/SinCos_block.vhd.
### Working on hdlcoder_sincos_control/SinCos as hdl_prj/hdlsrc/hdlcoder_sincos_control/SinCos.vhd.
### Generating package file hdl_prj/hdlsrc/hdlcoder_sincos_control/SinCos_pkg.vhd.
### Code Generation for 'hdlcoder_sincos_control' completed.
### Creating HDL Code Generation Check Report file:///tmp/Bdoc21b_1757077_221275/tpcf1538dd/hdl_prj/hdlsrc/hdlcoder_sincos_control/SinCos_report.html
### HDL check for 'hdlcoder_sincos_control' complete with 0 errors, 0 warnings, and 3 messages.
### HDL code generation complete.

SinCos Block Synthesis Performance

Following digrams shows the SinCos block synthesis performance on the Xilinx Virtex 7 and intel Stratix V devices.

Reciprocal Block with Control Signals

Each port of the Reciprocal block is as explained below.

When you open the Reciprocal block, it uses MATLAB Function blocks for the data and valid lines. This is as shown below.

open_system('hdlcoder_reciprocal_shiftadd_control')
open_system('hdlcoder_reciprocal_shiftadd_control/Reciprocal')

Example using Control Signal based Reciprocal Block

This section shows how to implement an example using control signal based Reciprocal block and generate HDL code by using HDL Coder™.

Open and Run Simulink Model

Before opening the model, set the input as follows. You can chose to set different input as per your requirement. This example uses following inputs which is linear.

reciprocal_input = fi(1/2^17:1/2^17:1,0,18,17)';

Specify the wordlength for fixed-point datatypes and the pipeline latency for the model. Go through the documentation for latency calculation.

WL_recip = 18;  recip_latency = 22;

Open the model hdlcoder_reciprocal_shiftadd_control and specify sufficient stop time that required to process all the input combinations.

stoptime_recip = length(reciprocal_input)-1+recip_latency;
open_system('hdlcoder_reciprocal_shiftadd_control')
sim('hdlcoder_reciprocal_shiftadd_control')

You can see the below waveform when you simulate the above model. You can see that dataOut is valid when validOut is high.

Validate Simulink Output By Using Reference Output

To validate the output obtained by simulating the Simulink model, you can compare the Simulink output with a reference output. To obtain the reference output, use the sqrt function.

Compute the reference output by using the reciprocal operation.

ref_reciprocal = 1./double(reciprocal_input);

Use logical indexing to extract valid output.

implementation_reciprocal = simulink_reciprocal(valid_output);

To validate the output, plot the comparison results by using the comparison_plot_reciprocal function in this example. You can see that the maximum error observed from the comparison results is quite small.

comparison_plot_reciprocal(ref_reciprocal,implementation_reciprocal,9,'reciprocal linear input');
Maximum Error reciprocal linear input 9.999771e-01 
Maximum PctError reciprocal linear input 4.999924e+01 

Generate HDL Code for Reciprocal Implementation

Before you generate code, you can see the HDL settings saved on the model by using the hdlsaveparams function.

hdlsaveparams('hdlcoder_reciprocal_shiftadd_control')
%% Set Model 'hdlcoder_reciprocal_shiftadd_control' HDL parameters
hdlset_param('hdlcoder_reciprocal_shiftadd_control', 'Backannotation', 'on');
hdlset_param('hdlcoder_reciprocal_shiftadd_control', 'HDLSubsystem', 'hdlcoder_reciprocal_shiftadd_control/Reciprocal');
hdlset_param('hdlcoder_reciprocal_shiftadd_control', 'ResetType', 'Synchronous');
hdlset_param('hdlcoder_reciprocal_shiftadd_control', 'ResourceReport', 'on');
hdlset_param('hdlcoder_reciprocal_shiftadd_control', 'SynthesisTool', 'Xilinx Vivado');
hdlset_param('hdlcoder_reciprocal_shiftadd_control', 'SynthesisToolChipFamily', 'Virtex7');
hdlset_param('hdlcoder_reciprocal_shiftadd_control', 'SynthesisToolDeviceName', 'xc7v2000t');
hdlset_param('hdlcoder_reciprocal_shiftadd_control', 'SynthesisToolPackageName', 'fhg1761');
hdlset_param('hdlcoder_reciprocal_shiftadd_control', 'SynthesisToolSpeedValue', '-2');
hdlset_param('hdlcoder_reciprocal_shiftadd_control', 'TargetDirectory', 'hdl_prj\hdlsrc');
hdlset_param('hdlcoder_reciprocal_shiftadd_control', 'TargetFrequency', 500);
hdlset_param('hdlcoder_reciprocal_shiftadd_control', 'Traceability', 'on');

% Set SubSystem HDL parameters
hdlset_param('hdlcoder_reciprocal_shiftadd_control/Reciprocal', 'FlattenHierarchy', 'on');

hdlset_param('hdlcoder_reciprocal_shiftadd_control/Reciprocal/LumpLatency', 'Architecture', 'MATLAB Datapath');
% Set SubSystem HDL parameters
hdlset_param('hdlcoder_reciprocal_shiftadd_control/Reciprocal/LumpLatency', 'FlattenHierarchy', 'on');

hdlset_param('hdlcoder_reciprocal_shiftadd_control/Reciprocal/Reciprocal', 'Architecture', 'ShiftAdd');

hdlset_param('hdlcoder_reciprocal_shiftadd_control/Reciprocal/ValidLine', 'Architecture', 'MATLAB Datapath');
% Set SubSystem HDL parameters
hdlset_param('hdlcoder_reciprocal_shiftadd_control/Reciprocal/ValidLine', 'FlattenHierarchy', 'on');

To generate HDL code for the Reciprocal block in the model, use the makehdl function.

makehdl('hdlcoder_reciprocal_shiftadd_control/Reciprocal')
close_system('hdlcoder_reciprocal_shiftadd_control')
close all;
### Generating HDL for 'hdlcoder_reciprocal_shiftadd_control/Reciprocal'.
### Using the config set for model <a href="matlab:configset.showParameterGroup('hdlcoder_reciprocal_shiftadd_control', { 'HDL Code Generation' } )">hdlcoder_reciprocal_shiftadd_control</a> for HDL code generation parameters.
### Running HDL checks on the model 'hdlcoder_reciprocal_shiftadd_control'.
### Begin compilation of the model 'hdlcoder_reciprocal_shiftadd_control'...
### Applying HDL optimizations on the model 'hdlcoder_reciprocal_shiftadd_control'...
### <a href="matlab:configset.internal.open('hdlcoder_reciprocal_shiftadd_control','AdaptivePipelining')">'AdaptivePipelining'</a> is set to 'Off' for the model. 'AdaptivePipelining' can improve the achievable clock frequency and reduce the area usage on FPGA boards. To enable adaptive pipelining, set the option to 'On'. When adaptive pipelining is enabled, it inserts pipeline registers to create patterns that efficiently map blocks to DSP units on the target FPGA device.
### <a href="matlab:configset.internal.open('hdlcoder_reciprocal_shiftadd_control','LUTMapToRAM')">'LUTMapToRAM'</a> is set to 'On' for the model. This option is used to map lookup tables to a block RAM in hardware.  To disable pipeline insertion for mapping lookup tables to RAM, set the option to 'Off'.
### Begin model generation.
### Model generation complete.
### Begin VHDL Code Generation for 'hdlcoder_reciprocal_shiftadd_control'.
### Working on hdlcoder_reciprocal_shiftadd_control/Reciprocal/Reciprocal as hdl_prj/hdlsrc/hdlcoder_reciprocal_shiftadd_control/Reciprocal_block.vhd.
### Working on hdlcoder_reciprocal_shiftadd_control/Reciprocal as hdl_prj/hdlsrc/hdlcoder_reciprocal_shiftadd_control/Reciprocal.vhd.
### Code Generation for 'hdlcoder_reciprocal_shiftadd_control' completed.
### Generating HTML files for code generation report at <a href="matlab:web('/tmp/Bdoc21b_1757077_221275/tpcf1538dd/hdl_prj/hdlsrc/hdlcoder_reciprocal_shiftadd_control/html/hdlcoder_reciprocal_shiftadd_control_codegen_rpt.html');">hdlcoder_reciprocal_shiftadd_control_codegen_rpt.html</a>
### Creating HDL Code Generation Check Report file:///tmp/Bdoc21b_1757077_221275/tpcf1538dd/hdl_prj/hdlsrc/hdlcoder_reciprocal_shiftadd_control/Reciprocal_report.html
### HDL check for 'hdlcoder_reciprocal_shiftadd_control' complete with 0 errors, 0 warnings, and 2 messages.
### HDL code generation complete.

Reciprocal Block Synthesis Perfromance

Following digrams shows the Reciprocal block synthesis performance on the Xilinx Virtex 7 and intel Stratix V devices.

Divide Block with Control Signals

Each port of the Divide block is as explained below.

When you open the Divide block, it uses MATLAB Function blocks for the data and valid lines. This is as shown below.

open_system('hdlcoder_divide_shiftadd_control')
open_system('hdlcoder_divide_shiftadd_control/Divide')

Example using Control Signal based Divide Block

This section shows how to implement an example using control signal based Divide block and generate HDL code by using HDL Coder™.

Open and Run Simulink Model

Before opening the model, set the input as follows. You can chose to set different input as per your requirement. This example uses following inputs which is linear.

dividend_input = fi(1/2^17:1/2^17:1,0,18,17)';
divisor_input = fi(1/2^17:1/2^17:1,0,18,13)';

Specify the wordlength for fixed-point datatypes and the pipeline latency for the model. Go through the documentation for latency calculation.

WL_divide = 18;  divide_latency = 22;

Open the model hdlcoder_divide_shiftadd_control and specify sufficient stop time that required to process all the input combinations.

stoptime_divide = length(dividend_input)-1+divide_latency;
open_system('hdlcoder_divide_shiftadd_control')
sim('hdlcoder_divide_shiftadd_control')

You can see the below waveform when you simulate the above model. You can see that dataOut is valid when validOut is high.

Validate Simulink Output By Using Reference Output

To validate the output obtained by simulating the Simulink model, you can compare the Simulink output with a reference output. To obtain the reference output, use the sqrt function.

Compute the reference output by using the divide function.

ref_divide = double(dividend_input)./double(divisor_input);

Use logical indexing to extract valid output.

implementation_divide = simulink_divide(valid_output);

To validate the output, plot the comparison results by using the comparison_plot_divide function in this example. You can see that the maximum error observed from the comparison results is quite small.

comparison_plot_divide(ref_divide,implementation_divide,11,'divide linear input');
Maximum Error divide linear input Inf 
Maximum PctError divide linear input 6.249285e+00 

Generate HDL Code for Divide Implementation

Before you generate code, you can see the HDL settings saved on the model by using the hdlsaveparams function.

hdlsaveparams('hdlcoder_divide_shiftadd_control')
%% Set Model 'hdlcoder_divide_shiftadd_control' HDL parameters
hdlset_param('hdlcoder_divide_shiftadd_control', 'Backannotation', 'on');
hdlset_param('hdlcoder_divide_shiftadd_control', 'HDLSubsystem', 'hdlcoder_divide_shiftadd_control/Divide');
hdlset_param('hdlcoder_divide_shiftadd_control', 'ResetType', 'Synchronous');
hdlset_param('hdlcoder_divide_shiftadd_control', 'ResourceReport', 'on');
hdlset_param('hdlcoder_divide_shiftadd_control', 'SynthesisTool', 'Xilinx Vivado');
hdlset_param('hdlcoder_divide_shiftadd_control', 'SynthesisToolChipFamily', 'Virtex7');
hdlset_param('hdlcoder_divide_shiftadd_control', 'SynthesisToolDeviceName', 'xc7v2000t');
hdlset_param('hdlcoder_divide_shiftadd_control', 'SynthesisToolPackageName', 'fhg1761');
hdlset_param('hdlcoder_divide_shiftadd_control', 'SynthesisToolSpeedValue', '-2');
hdlset_param('hdlcoder_divide_shiftadd_control', 'TargetDirectory', 'hdl_prj\hdlsrc');
hdlset_param('hdlcoder_divide_shiftadd_control', 'TargetFrequency', 500);
hdlset_param('hdlcoder_divide_shiftadd_control', 'Traceability', 'on');

% Set SubSystem HDL parameters
hdlset_param('hdlcoder_divide_shiftadd_control/Divide', 'FlattenHierarchy', 'on');

hdlset_param('hdlcoder_divide_shiftadd_control/Divide/Divide', 'Architecture', 'ShiftAdd');

hdlset_param('hdlcoder_divide_shiftadd_control/Divide/LumpLatency', 'Architecture', 'MATLAB Datapath');
% Set SubSystem HDL parameters
hdlset_param('hdlcoder_divide_shiftadd_control/Divide/LumpLatency', 'FlattenHierarchy', 'on');

hdlset_param('hdlcoder_divide_shiftadd_control/Divide/ValidLine', 'Architecture', 'MATLAB Datapath');
% Set SubSystem HDL parameters
hdlset_param('hdlcoder_divide_shiftadd_control/Divide/ValidLine', 'FlattenHierarchy', 'on');

To generate HDL code for the Divide block in the model, use the makehdl function.

makehdl('hdlcoder_divide_shiftadd_control/Divide')
close_system('hdlcoder_divide_shiftadd_control')
close all;
### Generating HDL for 'hdlcoder_divide_shiftadd_control/Divide'.
### Using the config set for model <a href="matlab:configset.showParameterGroup('hdlcoder_divide_shiftadd_control', { 'HDL Code Generation' } )">hdlcoder_divide_shiftadd_control</a> for HDL code generation parameters.
### Running HDL checks on the model 'hdlcoder_divide_shiftadd_control'.
### Begin compilation of the model 'hdlcoder_divide_shiftadd_control'...
### Applying HDL optimizations on the model 'hdlcoder_divide_shiftadd_control'...
### <a href="matlab:configset.internal.open('hdlcoder_divide_shiftadd_control','AdaptivePipelining')">'AdaptivePipelining'</a> is set to 'Off' for the model. 'AdaptivePipelining' can improve the achievable clock frequency and reduce the area usage on FPGA boards. To enable adaptive pipelining, set the option to 'On'. When adaptive pipelining is enabled, it inserts pipeline registers to create patterns that efficiently map blocks to DSP units on the target FPGA device.
### <a href="matlab:configset.internal.open('hdlcoder_divide_shiftadd_control','LUTMapToRAM')">'LUTMapToRAM'</a> is set to 'On' for the model. This option is used to map lookup tables to a block RAM in hardware.  To disable pipeline insertion for mapping lookup tables to RAM, set the option to 'Off'.
### Begin model generation.
### Model generation complete.
### Begin VHDL Code Generation for 'hdlcoder_divide_shiftadd_control'.
### Working on hdlcoder_divide_shiftadd_control/Divide/Divide as hdl_prj/hdlsrc/hdlcoder_divide_shiftadd_control/Divide_block.vhd.
### Working on hdlcoder_divide_shiftadd_control/Divide as hdl_prj/hdlsrc/hdlcoder_divide_shiftadd_control/Divide.vhd.
### Code Generation for 'hdlcoder_divide_shiftadd_control' completed.
### Generating HTML files for code generation report at <a href="matlab:web('/tmp/Bdoc21b_1757077_221275/tpcf1538dd/hdl_prj/hdlsrc/hdlcoder_divide_shiftadd_control/html/hdlcoder_divide_shiftadd_control_codegen_rpt.html');">hdlcoder_divide_shiftadd_control_codegen_rpt.html</a>
### Creating HDL Code Generation Check Report file:///tmp/Bdoc21b_1757077_221275/tpcf1538dd/hdl_prj/hdlsrc/hdlcoder_divide_shiftadd_control/Divide_report.html
### HDL check for 'hdlcoder_divide_shiftadd_control' complete with 0 errors, 0 warnings, and 2 messages.
### HDL code generation complete.

Divide Block Synthesis Performance

Following digrams shows the Divide block synthesis performance on the Xilinx Virtex 7 and intel Stratix V devices.