System Toolbox blocks that have fixed-point support usually allow you to specify fixed-point characteristics through block parameters. By specifying data type and scaling information for these fixed-point parameters, you can simulate your target hardware more closely.
Note: Floating-point inheritance takes precedence over the settings discussed in this section. When the block has floating-point input, all block data types match the input. |
You can find most fixed-point parameters on the Data Types pane of System Toolbox blocks. The following figure shows a typical Data Types pane.
All System Toolbox blocks with fixed-point capabilities share a set of common parameters, but each block can have a different subset of these fixed-point parameters. The following table provides an overview of the most common fixed-point block parameters.
Fixed-Point Data Type Parameter | Description |
---|---|
Rounding Mode | Specifies the rounding mode for the block to use when the specified data type and scaling cannot exactly represent the result of a fixed-point calculation. See Rounding Modes for more information on the available options. |
Overflow Mode | Specifies the overflow mode to use when the result of a fixed-point calculation does not fit into the representable range of the specified data type. See Overflow Handling for more information on the available options. |
Intermediate Product | Specifies the data type and scaling of the intermediate product for fixed-point blocks. Blocks that feed multiplication results back to the input of the multiplier use the intermediate product data type. See the reference page of a specific block to learn about the intermediate product data type for that block. |
Product Output | Specifies the data type and scaling of the product output for fixed-point blocks that must compute multiplication results. See the reference page of a specific block to learn about the product output data type for that block. For or complex-complex multiplication, the multiplication result is in the accumulator data type. See Multiplication Data Types for more information on complex fixed-point multiplication in System toolbox software. |
Accumulator | Specifies the data type and scaling of the accumulator (sum) for fixed-point blocks that must hold summation results for further calculation. Most such blocks cast to the accumulator data type before performing the add operations (summation). See the reference page of a specific block for details on the accumulator data type of that block. |
Output | Specifies the output data type and scaling for blocks. |
The Data Type Assistant is an interactive graphical tool available on the Data Types pane of some fixed-point System Toolbox blocks.
To learn more about using the Data Type Assistant to help you specify block data type parameters, see the following section of the Simulink^{®} documentation:
Specify Data Types Using Data Type Assistant |
Some fixed-point System Toolbox blocks have Minimum and Maximum parameters on the Data Types pane. When a fixed-point data type has these parameters, you can use them to specify appropriate minimum and maximum values for range checking purposes.
To learn how to specify signal ranges and enable signal range checking, see Signal Ranges in the Simulink documentation.
You can monitor and control fixed-point settings for System Toolbox blocks at a system or subsystem level with the Fixed-Point Tool. For additional information on these subjects, see
The fxptdlg
reference
page — A reference page on the Fixed-Point Tool in the Simulink documentation
Fixed-Point Tool — A tutorial that highlights the use of the Fixed-Point Tool in the Fixed-Point Designer™ software documentation
The Fixed-Point Tool logs overflows, saturations, and simulation
minimums and maximums for fixed-point System Toolbox blocks. The Fixed-Point
Tool does not log overflows and saturations when the Data
overflow
line in the Diagnostics > Data
Integrity pane of the Configuration Parameters dialog
box is set to None
.
You can use the Fixed-Point Tool autoscaling feature to set the scaling for System Toolbox fixed-point data types.
System Toolbox blocks obey the Use local settings
, Double
, Single
,
and Off
modes of the Data type
override parameter in the Fixed-Point Tool. The Scaled double
mode is also supported for System
Toolboxes source and byte-shuffling blocks, and for some arithmetic
blocks such as Difference and Normalization.
Selecting appropriate word lengths and scalings for the fixed-point
parameters in your model can be challenging. To aid you, an Inherit
via internal rule
choice is often available for fixed-point
block data type parameters, such as the Accumulator and Product
output signals. The following sections describe how the
word and fraction lengths are selected for you when you choose Inherit
via internal rule
for a fixed-point block data type
parameter in System Toolbox software:
Note: In the equations in the following sections, WL = word length and FL = fraction length. |
The internal rule for accumulator data types first calculates the ideal, full-precision result. Where N is the number of addends:
$$W{L}_{idealaccumulator}=W{L}_{inputtoaccumulator}+\mathrm{floor}({\mathrm{log}}_{2}(N-1))+1$$
$$F{L}_{idealaccumulator}=F{L}_{inputtoaccumulator}$$
For example, consider summing all the elements of a vector of length 6 and data type sfix10_En8. The ideal, full-precision result has a word length of 13 and a fraction length of 8.
The accumulator can be real or complex. The preceding equations are used for both the real and imaginary parts of the accumulator. For any calculation, after the full-precision result is calculated, the final word and fraction lengths set by the internal rule are affected by your particular hardware. See The Effect of the Hardware Implementation Pane on the Internal Rule for more information.
The internal rule for product data types first calculates the ideal, full-precision result:
$$W{L}_{idealproduct}=W{L}_{input1}+W{L}_{input2}$$
$$F{L}_{idealproduct}=F{L}_{input1}+F{L}_{input2}$$
For example, multiplying together the elements of a real vector of length 2 and data type sfix10_En8. The ideal, full-precision result has a word length of 20 and a fraction length of 16.
For real-complex multiplication, the ideal word length and fraction length is used for both the complex and real portion of the result. For complex-complex multiplication, the ideal word length and fraction length is used for the partial products, and the internal rule for accumulator data types described above is used for the final sums. For any calculation, after the full-precision result is calculated, the final word and fraction lengths set by the internal rule are affected by your particular hardware. See The Effect of the Hardware Implementation Pane on the Internal Rule for more information.
A few System Toolbox blocks have an Inherit via
internal rule
choice available for the block output.
The internal rule used in these cases is block-specific, and the equations
are listed in the block reference page.
As with accumulator and product data types, the final output word and fraction lengths set by the internal rule are affected by your particular hardware, as described in The Effect of the Hardware Implementation Pane on the Internal Rule.
The internal rule selects word lengths and fraction lengths that are appropriate for your hardware. To get the best results using the internal rule, you must specify the type of hardware you are using on the Hardware Implementation pane of the Configuration Parameters dialog box. You can open this dialog box from the Simulation menu in your model.
ASIC/FPGA. On an ASIC/FPGA target, the ideal, full-precision word length and fraction length calculated by the internal rule are used. If the calculated ideal word length is larger than the largest allowed word length, you receive an error. The largest word length allowed for Simulink and System Toolbox software is 128 bits.
Other targets. For all targets other than ASIC/FPGA, the ideal, full-precision word length calculated by the internal rule is rounded up to the next available word length of the target. The calculated ideal fraction length is used, keeping the least-significant bits.
If the calculated ideal word length for a product data type is larger than the largest word length on the target, you receive an error. If the calculated ideal word length for an accumulator or output data type is larger than the largest word length on the target, the largest target word length is used.
The following sections show examples of how the internal rule interacts with the Hardware Implementation pane to calculate accumulator data types and product data types.
Accumulator Data Types. Consider the following model ex_internalRule_accumExpex_internalRule_accumExp.
In the Difference blocks, the Accumulator parameter
is set to Inherit: Inherit via internal rule
,
and the Output parameter is set to Inherit:
Same as accumulator
. Therefore, you can see the accumulator
data type calculated by the internal rule on the output signal in
the model.
In the preceding model, the Device type parameter
in the Hardware Implementation pane of
the Configuration Parameters dialog box is set to ASIC/FPGA
.
Therefore, the accumulator data type used by the internal rule is
the ideal, full-precision result.
Calculate the full-precision word length for each of the Difference blocks in the model:
$$\begin{array}{l}W{L}_{idealaccumulator}=W{L}_{inputtoaccumulator}+\mathrm{floor}({\mathrm{log}}_{2}(numberofaccumulations))+1\\ W{L}_{idealaccumulator}=9+\mathrm{floor}({\mathrm{log}}_{2}(1))+1\\ W{L}_{idealaccumulator}=9+0+1=10\\ \\ W{L}_{idealaccumulator1}=W{L}_{inputtoaccumulator1}+\mathrm{floor}({\mathrm{log}}_{2}(numberofaccumulations))+1\\ W{L}_{idealaccumulator1}=16+\mathrm{floor}({\mathrm{log}}_{2}(1))+1\\ W{L}_{idealaccumulator1}=16+0+1=17\\ \\ W{L}_{idealaccumulator2}=W{L}_{inputtoaccumulator2}+\mathrm{floor}({\mathrm{log}}_{2}(numberofaccumulations))+1\\ W{L}_{idealaccumulator2}=127+\mathrm{floor}({\mathrm{log}}_{2}(1))+1\\ W{L}_{idealaccumulator2}=127+0+1=128\end{array}$$
Calculate the full-precision fraction length, which is the same for each Matrix Sum block in this example:
$$\begin{array}{l}F{L}_{idealaccumulator}=F{L}_{inputtoaccumulator}\\ F{L}_{idealaccumulator}=4\end{array}$$
Now change the Device type parameter in
the Hardware Implementation pane of the
Configuration Parameters dialog box to 32–bit
Embedded Processor
, by changing the parameters as shown
in the following figure.
As you can see in the dialog box, this device has 8-, 16-, and 32-bit word lengths available. Therefore, the ideal word lengths of 10, 17, and 128 bits calculated by the internal rule cannot be used. Instead, the internal rule uses the next largest available word length in each case You can see this if you rerun the model, as shown in the following figure.
Product Data Types. Consider the following model ex_internalRule_prodExpex_internalRule_prodExp.
In the Array-Vector Multiply blocks,
the Product Output parameter is set to Inherit:
Inherit via internal rule
, and the Output parameter
is set to Inherit: Same as product output
.
Therefore, you can see the product output data type calculated by
the internal rule on the output signal in the model. The setting of
the Accumulator parameter does not matter because
this example uses real values.
For the preceding model, the Device type parameter
in the Hardware Implementation pane of
the Configuration Parameters dialog box is set to ASIC/FPGA
.
Therefore, the product data type used by the internal rule is the
ideal, full-precision result.
Calculate the full-precision word length for each of the Array-Vector Multiply blocks in the model:
$$\begin{array}{l}W{L}_{idealproduct}=W{L}_{inputa}+W{L}_{inputb}\\ W{L}_{idealproduct}=7+5=12\\ \\ W{L}_{idealproduct1}=W{L}_{inputa}+W{L}_{inputb}\\ W{L}_{idealproduct1}=16+15=31\end{array}$$
Calculate the full-precision fraction length, which is the same for each Array-Vector Multiply block in this example:
$$\begin{array}{l}F{L}_{idealaccumulator}=F{L}_{inputtoaccumulator}\\ F{L}_{idealaccumulator}=4\end{array}$$
Now change the Device type parameter in
the Hardware Implementation pane of the
Configuration Parameters dialog box to 32–bit
Embedded Processor
, as shown in the following figure.
As you can see in the dialog box, this device has 8-, 16-, and 32-bit word lengths available. Therefore, the ideal word lengths of 12 and 31 bits calculated by the internal rule cannot be used. Instead, the internal rule uses the next largest available word length in each case. You can see this if you rerun the model, as shown in the following figure.
The following sections show you how to use the Fixed-Point Tool
to select appropriate data types for fixed-point blocks in the ex_fixedpoint_tut
model:
Open the model by typing ex_fixedpoint_tutex_fixedpoint_tut at the MATLAB^{®} command line.
This model uses the Cumulative Sum block to sum the input coming from the Fixed-Point Sources subsystem. The Fixed-Point Sources subsystem outputs two signals with different data types:
The Signed source has a word length of 16 bits and a fraction length of 15 bits.
The Unsigned source has a word length of 16 bits and a fraction length of 16 bits.
Run the model to check for overflow. MATLAB displays the following warnings at the command line:
Warning: Overflow occurred. This originated from 'ex_fixedpoint_tut/Signed Cumulative Sum'. Warning: Overflow occurred. This originated from 'ex_fixedpoint_tut/Unsigned Cumulative Sum'.
According to these warnings, overflow occurs in both Cumulative Sum blocks.
To investigate the overflows in this model, use the Fixed-Point
Tool. You can open the Fixed-Point Tool by selecting Tools > Fixed-Point > Fixed-Point Tool from the
model menu. Turn on logging for all blocks in your model by setting
the Fixed-point instrumentation mode parameter
to Minimums, maximums and overflows
.
Now that you have turned on logging, rerun the model by clicking the Simulation button.
The results of the simulation appear in a table in the central Contents pane of the Fixed-Point Tool. Review the following columns:
Name — Provides the name
of each signal in the following format: Subsystem Name/Block
Name: Signal Name
.
SimDT — The simulation data type of each logged signal.
SpecifiedDT — The data type specified on the block dialog for each signal.
SimMin — The smallest representable value achieved during simulation for each logged signal.
SimMax — The largest representable value achieved during simulation for each logged signal.
OverflowWraps — The number of overflows that wrap during simulation.
For more information on each of the columns in this table, see
the Contents Pane section
of the Simulink fxptdlg
function reference
page.
You can also see that the SimMin and SimMax values
for the Accumulator data types range from 0
to .9997
.
The logged results indicate that 8,192 overflows wrapped during simulation
in the Accumulator data type of the Signed Cumulative Sum block. Similarly,
the Accumulator data type of the Unsigned Cumulative Sum block had
16,383 overflows wrap during simulation.
To get more information about each of these data types, highlight them in the Contents pane, and click the Show details for selected result button ( )
Assume a target hardware that supports 32-bit integers,
and set the Accumulator word length in both Cumulative Sum blocks
to 32
. To do so, perform the following steps:
Right-click the Signed Cumulative Sum: Accumulator
row
in the Fixed-Point Tool pane, and select Highlight Block
In Model.
Double-click the block in the model, and select the Data Types pane of the dialog box.
Open the Data Type Assistant for Accumulator by clicking the Assistant button ( ) in the Accumulator data type row.
Set the Mode to Fixed
Point
. To see the representable range of the current
specified data type, click the Fixed-point details link.
The tool displays the representable maximum and representable minimum
values for the current data type.
Change the Word length to 32
,
and click the Refresh details button in the Fixed-point
details section to see the updated representable range.
When you change the value of the Word length parameter,
the data type string in the Data Type edit box
automatically updates.
Click OK on the block dialog box to save your changes and close the window.
Set the word length of the Accumulator data type of
the Unsigned Cumulative Sum block to 32
bits. You
can do so in one of two ways:
Type the data type string fixdt([],32,0)
directly
into Data Type edit box for the Accumulator data
type parameter.
Perform the same steps you used to set the word length
of the Accumulator data type of the Signed Cumulative Sum block to 32
bits.
To verify your changes in word length and check for overflow, rerun your model. To do so, click the Simulate button in the Fixed-Point Tool.
The Contents pane of the Fixed-Point Tool
updates, and you can see that no overflows occurred in the most recent
simulation. However, you can also see that the SimMin and SimMax values
range from 0
to 0
. This underflow
happens because the fraction length of the Accumulator data type is
too small. The SpecifiedDT cannot represent the
precision of the data values. The following sections discuss how to
find a floating-point benchmark and use the Fixed-Point Tool to propose
fraction lengths.
The Data type override feature of the Fixed-Point
tool allows you to override the data types specified in your model
with floating-point types. Running your model in Double
override
mode gives you a reference range to help you select appropriate fraction
lengths for your fixed-point data types. To do so, perform the following
steps:
Open the Fixed-Point Tool and set Data type
override to Double
.
Run your model by clicking the Run simulation and store active results button.
Examine the results in the Contents pane
of the Fixed-Point Tool. Because you ran the model in Double
override
mode, you get an accurate, idealized representation of the simulation
minimums and maximums. These values appear in the SimMin and SimMax parameters.
Now that you have an accurate reference representation
of the simulation minimum and maximum values, you can more easily
choose appropriate fraction lengths. Before making these choices,
save your active results to reference so you can use them as your
floating-point benchmark. To do so, select Results > Move Active Results To Reference from
the Fixed-Point Tool menu. The status displayed in the Run column
changes from Active
to Reference
for
all signals in your model.
Now that you have your Double
override
results saved as a floating-point reference, you are ready to propose
fraction lengths.
To propose fraction lengths for your data types, you must
have a set of Active
results available in the Fixed-Point
Tool. To produce an active set of results, simply rerun your model.
The tool now displays both the Active
results and
the Reference
results for each signal.
Select the Use simulation min/max if design min/max is not available check box. You did not specify any design minimums or maximums for the data types in this model. Thus, the tool uses the logged information to compute and propose fraction lengths. For information on specifying design minimums and maximums, see Signal Ranges in the Simulink documentation.
Click the Propose fraction lengths button ( ). The tool populates the proposed data types in the ProposedDT column of the Contents pane. The corresponding proposed minimums and maximums are displayed in the ProposedMin and ProposedMax columns.
Before accepting the fraction lengths proposed by the Fixed-Point Tool, it is important to look at the details of that data type. Doing so allows you to see how much of your data the suggested data type can represent. To examine the suggested data types and accept the proposed scaling, perform the following steps:
In the Contents pane of the Fixed-Point Tool, you can see the proposed fraction lengths for the data types in your model.
The proposed fraction length for the Accumulator data type of both the Signed and Unsigned Cumulative Sum blocks is 17 bits.
To get more details about the proposed scaling for a particular data type, highlight the data type in the Contents pane of the Fixed-Point Tool.
Open the Autoscale Information window for the highlighted data type by clicking the Show autoscale information for the selected result button ( ).
When the Autoscale Information window opens, check the Value and Percent Proposed Representable columns for the Simulation Minimum and Simulation Maximum parameters. You can see that the proposed data type can represent 100% of the range of simulation data.
To accept the proposed data types, select the check box in the Accept column for each data type whose proposed scaling you want to keep. Then, click the Apply accepted fraction lengths button ( ). The tool updates the specified data types on the block dialog boxes and the SpecifiedDT column in the Contents pane.
To verify the newly accepted scaling, set the Data type override parameter back to Use local settings, and run the model. Looking at Contents pane of the Fixed-Point Tool, you can see the following details:
The SimMin and SimMax values
of the Active
run match the SimMin and SimMax values
from the floating-point Reference
run.
There are no longer any overflows.
The SimDT does not match the SpecifiedDT for
the Accumulator data type of either Cumulative Sum block. This difference
occurs because the Cumulative Sum block always inherits its Signedness from
the input signal and only allows you to specify a Signedness of Auto
.
Therefore, the SpecifiedDT for both Accumulator
data types is fixdt([],32,17)
. However, because
the Signed Cumulative Sum block has a signed input signal, the SimDT for
the Accumulator parameter of that block is also signed (fixdt(1,32,17)
).
Similarly, the SimDT for the Accumulator parameter
of the Unsigned Cumulative Sum block inherits its Signedness from
its input signal and thus is unsigned (fixdt(0,32,17)
).