coder.MexCodeConfig

Configuration parameters for MEX function generation from MATLAB code

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Description

A coder.MexCodeConfig object contains the configuration parameters that codegen uses when generating a MEX function. Pass the object to the codegen function by using the -config option.

Creation

Create a coder.MexCodeConfig object by using the coder.config function.

Once you create a coder.MexCodeConfig object, you can modify its properties programmatically at the command line or interactively by using the Configuration Parameter Dialog Box. See Specify Code Configuration Parameters Interactively.

Properties

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Dynamic array optimization, specified as true or false. For more information, see Cache dynamic array data.

Formatting tool for the generated code, specified as 'Auto', 'Clang-format', or 'MathWorks'. For more information, see Select code format tool to use.

Maximum number of function specializations for compile-time recursion, specified as a positive integer. For more information, see Compile-time recursion limit.

Maximum number of instructions that the constant folder executes, specified as a positive integer. For more information, see Constant folding timeout.

Constant input checking mode, specified as 'CheckValues' or 'IgnoreValues'. For more information, see Constant inputs.

Whether to generate C++ code that contains enumeration classes, specified as true or false. For more information, see Generate C++ enum class from MATLAB enumeration.

Namespace for the generated C++ code, specified as a character vector. For more information, see C++ namespace.

Place C++ code generated for MathWorks code, specified as a character vector. For more information, see Namespace for MathWorks code.

Whether to generate C++ classes or C style structures for MATLAB classes, specified as true or false. For more information, see Generate C++ classes from MATLAB classes.

Whether to generate C++ namespaces for the namespaces in your MATLAB code, specified as true or false. For more information, see Generate C++ namespaces from MATLAB namespaces.

Custom code that appears near the top of each C/C++ header file generated from your MATLAB code, except rtwtypes.h and rtwhalf.h, specified as a character vector. For more information, see Header file.

Include folders to add to the include path when compiling the generated code, specified as a string array, cell array of character vectors, or character vector. For more information, see Additional include directories.

Custom code to include in the generated initialize function, specified as a character vector. For more information, see Initialize function.

Static library files to link with the generated code, specified as a string array, cell array of character vectors, or character vector. For more information, see Additional libraries.

Source files to compile and link with the generated code, specified as a string array, cell array of character vector, or character vector. For more information, see Additional source files.

Specify code to appear near the top of each generated .c or .cpp file (except rtwhalf.c or rtwhalf.cpp), outside of any function, specified as a character vector. For more information, see Source file.

Code that appears in the generated terminate function, specified as a character vector. For more information, see Terminate function.

Configuration object for code generation for deep learning networks, specified as specified as one of the objects in this table.

ObjectRequiresDescription
coder.MklDNNConfig

  • Deep Learning Toolbox™

  • MATLAB Coder™ Interface for Deep Learning support package

A coder.MklDNNConfig object contains parameters specific to C++ code generation for deep learning using Intel® MKL-DNN. To create a coder.MklDNNConfig object, use coder.DeepLearningConfig. For example: 

cfg = coder.config('mex');
cfg.TargetLang = 'C++';
cfg.DeepLearningConfig = coder.DeepLearningConfig('mkldnn');

See Code Generation for Deep Learning Networks with MKL-DNN.

coder.CuDNNConfig (GPU Coder)

  • Deep Learning Toolbox

  • GPU Coder™

  • GPU Coder Interface for Deep Learning support package

A coder.CuDNNConfig object contains parameters specific to CUDA® code generation for deep learning using the cuDNN library. To create a coder.CuDNNConfig object, use coder.DeepLearningConfig. For example: 

cfg = coder.gpuConfig('lib');
cfg.TargetLang = 'C++';
cfg.DeepLearningConfig = coder.DeepLearningConfig('cudnn');

See Code Generation for Deep Learning Networks by Using cuDNN (GPU Coder).

coder.TensorRTConfig (GPU Coder)

  • Deep Learning Toolbox

  • GPU Coder

  • GPU Coder Interface for Deep Learning support package

A coder.TensorRTConfig object contains parameters specific to CUDA code generation for deep learning using the TensorRT library. To create a coder.TensorRTConfig object, use coder.DeepLearningConfig. For example: 

cfg = coder.gpuConfig('lib');
cfg.TargetLang = 'C++';
cfg.DeepLearningConfig = coder.DeepLearningConfig('tensorrt');

See Code Generation for Deep Learning Networks by Using TensorRT (GPU Coder).

Note

MEX code generation is not supported for deep learning using the ARM® Compute Library.

Dependency: If DeepLearningConfig is set, codegen sets TargetLang to C++.

Dynamic memory allocation mode, specified as one of the values in this table.

ValueDescription
'Threshold'

This value is the default value.

The code generator allocates memory dynamically on the heap for variable-size arrays whose size (in bytes) is greater than or equal to DynamicMemoryAllocationThreshold.

'AllVariableSizeArrays'The code generator dynamically allocates memory for all variable-size arrays on the heap.
'Off'

The code generator statically allocates memory for variable-size arrays on the stack.

Unbounded variable-size arrays require dynamic memory allocation.

Dependencies:

  • EnableVariableSizing enables this parameter.

  • Setting this DynamicMemoryAllocation to 'Threshold' enables the DynamicMemoryAllocationThreshold parameter.

See Generate Code for Variable-Size Arrays.

Note

DynamicMemoryAllocation configuration option will be removed in a future release. To dynamically allocation memory for variable-sized arrays, use the EnableDynamicMemoryAllocation option. To set the threshold, use the DynamicMemoryAllocationThreshold option.

Dynamic memory allocation for fixed-size arrays, specified as false or true. For more information, see Enable dynamic memory allocation for fixed-sized arrays.

Implementation of dynamically allocated array at the interface of the generated C/C++ function, specified as 'Auto', 'C', or 'C++'. For more information, see Dynamic memory allocation interface.

Size threshold for dynamic memory allocation of variable-size arrays, specified as a positive integer. For more information, see Dynamic memory allocation threshold.

Expression echoing, specified as true or false. For more information, see Echo expressions without terminating semicolons.

Automatic extrinsic function calls, specified as true or false. For more information, see Automatically introduce extrinsic calls.

Automatic parallelization of for loops, specified as false or true. For more information, see Enable automatic parallelization.

Reporting for automatic parallelization of for loops, specified as true or false. For more information, see Enable automatic parallelization reporting.

C compiler debugging mode, specified as false or true. For more information, see Enable C/C++ compiler debug mode.

Dynamic memory allocation for variable-size arrays, specified as true or false. For more information, see Enable dynamic memory allocation.

Implicit expansion capabilities in the generated code, specified as true or false. For more information, see Enable implicit expansion.

Just-in-time (JIT) compilation mode, specified as false or true. For more information, see Use JIT compilation for build type of MEX.

memcpy optimization, specified as true or false. For more information, see Use memcpy for vector assignment.

Instrumentation for profiling of generated MEX function, specified as false or true. For more information, see Enable execution profiling.

Parallelization of parfor-loops, specified as true or false. For more information, see Enable OpenMP library if possible.

Run-time recursion support, specified as true or false. For more information, see Enable run-time recursion.

Variable-size array support, specified as true or false. For more information, see Enable variable-sizing.

Extrinsic function call support, specified as true or false. For more information, see Keep extrinsic calls.

File partitioning mode, specified as 'MapMFileToCFile' 'SingleFile'. For more information, see Generated file partitioning method.

Generation of only source code, specified as true or false. For more information, see Generate code only.

Comments in generated code, specified as true or false. For more information, see Include comments.

Code generation report, specified false or true. For more information, see Always create a report.

Global data synchronization mode, specified as 'SyncAlways', 'SyncAtEntryAndExits', or 'NoSync'. For more information, see Global data synchronization mode.

Configuration object for generating CUDA GPU code using GPU Coder. A GpuCodeConfig object contains parameters specific to CUDA GPU code generation. To create a GpuCodeConfig object, use coder.gpuConfig (GPU Coder). For example: 

cfg = coder.gpuConfig('mex');
cfg.GpuConfig

ans = 

  GpuCodeConfig with properties:

                    Enabled: 1
                 MallocMode: 'discrete'
           KernelNamePrefix: ''
               EnableCUBLAS: 1
             EnableCUSOLVER: 1
                EnableCUFFT: 1
               Benchmarking: 0
                  SafeBuild: 0
          ComputeCapability: 'Auto'
    CustomComputeCapability: ''
              CompilerFlags: ''
        StackLimitPerThread: 1024
            MallocThreshold: 200
     MaximumBlocksPerKernel: 0
        EnableMemoryManager: 1
           SelectCudaDevice: -1

For more information, see Generate Code Using the Command Line Interface (GPU Coder).

If GpuConfig is set, the code generator uses fixed values for certain properties that are required for GPU code generation. Some properties also have different default values. For more information, see Configure GPU Code Generation (GPU Coder).

Whether to highlight potential issues resulting from implicit expansion in the code generation report, specified as true or false. For more information, see Highlight potential issues resulting from implicit expansion.

Whether to highlight potential issues resulting from the use of loop control functions in the code generation report, specified as true or false. For more information, see Highlight potential issues in use of coder.loop functions.

Potential row-major layout efficiency issues, specified true or false. For more information, see Highlight potential row-major issues.

Assignment of float and double zero with memset, specified true or false. For more information, see Use memset to initialize floats and doubles to 0.0.

Control inlining between MathWorks functions, specified as 'Speed', 'Always', 'Readability', or 'Never'. For more information, see Inline strategy for MathWorks written MATLAB functions.

Control inlining between user-written functions and MathWorks functions, specified as 'Speed', 'Always', 'Readability', or 'Never'. For more information, see Inline strategy for calls between MathWorks functions and user functions.

Control inlining between user-written functions, specified as 'Speed', 'Always', 'Readability', or 'Never'. For more information, see Inline strategy for user written MATLAB functions.

Memory integrity checking, specified as true or false. For more information, see Check memory integrity.

Whether the code generator embeds large constants for a deep neural network (DNN) in the generated source code or writes these constants to binary data files, specified as 'WriteOnlyDNNConstantsToDataFiles' or 'KeepInSourceFiles'. For more information, see Large constant generation.

Threshold above which the code generator writes DNN constants to binary data files, specified as a positive integer. For more information, see Large constant threshold.

Automatic open of code generation report, specified true or false. For more information, see Automatically launch a report if one is generated.

Inclusion of MATLAB source code as comments in generated code, specified true or false. For more information, see MATLAB source code as comments.

Minimum size for memcpy or memset optimization in bytes, specified as a positive integer. For more information, see Memcpy threshold (bytes).

Object name, specified as a character vector.

Maximum number of CPU threads to run parallel for-loops in the generated C/C++ code, specified as a positive integer. For more information, see Maximum number of CPU threads.

Generate SIMD code for reduction operations and parallelize for-loops performing reduction operations, specified as false or true. For more information, see Optimize reductions.

Command to customize build processing after MEX function generation with codegen, specified as a character vector. For more information, see Post-code-generation command.

Generation of code that uses N-dimensional indexing, specified false or true. For more information, see Preserve array dimensions.

Variable names to preserve in the generated code, specified as 'None', 'UserNames', 'All'. For more information, see Preserve variable names.

Name of variable containing code generation report information about code generation, specified as a character vector. For more information, see Export report information to variable.

Potential difference reporting, specified true or false. For more information, see Report differences from MATLAB.

Names that the code generator must not use for functions or variables, specified as a string array, cell array of character vectors, or character vector. For more information, see Reserved names.

Responsiveness checks, specified as true or false. For more information, see Enable responsiveness to CTRL+C and graphics refreshing.

Row-major array layout for the generated code, specified false or true. For more information, see Array layout.

Integer overflow support, specified true or false. For more information, see Saturate on integer overflow.

Level of SIMD intrinsics to use to accelerate vector operations, specified as 'Portable', 'Full', or 'None'. For more information, see Hardware SIMD acceleration.

Maximum stack usage per application in bytes, specified as a positive integer. For more information, see Stack usage max.

Language to use in generated code, specified as 'C' or 'C++'. For more information, see Language.

Since R2024b

Whether to use precompiled libraries in generated code, specified as 'Prefer' or 'Avoid'. For more information, see Use precompiled libraries.

Code generation progress display at the MATLAB command line, specified as 'Info', 'Silent', or 'Verbose'. For more information, see Show verbose compiler output.

Examples

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Write a MATLAB function from which you can generate code. This example uses the function myadd that returns the sum of its inputs.

function c = myadd(a,b)
c = a + b;
end

Create a configuration object for MEX function generation.

cfg = coder.config('mex');

Change the values of the properties for which you do not want to use the default values. For example, enable just-in-time (JIT) compilation.

cfg.EnableJIT = true;

Generate code by using codegen. Pass the configuration object to codegen by using the -config option. Specify that the input arguments are scalar double.

codegen myadd -config cfg -args {1 1} -report

Alternative Functionality

To use default configuration parameter values for MEX function generation, instead of creating a configuration object, you can call codegen without specifying a configuration object or with the -config:mex option.

Version History

Introduced in R2011a

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See Also

Functions

Objects

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