Ensure Transparency in parfor-Loops or spmd Statements

Ensure Transparency in `parfor`-Loops or `spmd` Statements

The body of a parfor-loop or spmd block must be transparent. Transparency means that all references to variables must be visible in the text of the code.

In the following examples, the variable X is not transferred to the workers. Only the character vector 'X' is passed to eval, and X is not visible as an input variable in the loop or block body. As a result, MATLAB^® issues an error at run time.

X = 5;
parfor ii = 1:4
    eval('X');
end

X = 5;
spmd
    eval('X');
end

Similarly, you cannot clear variables from a workspace by executing clear inside a parfor or spmd statement:

parfor ii = 1:4
    <statements...>
    clear('X')  % cannot clear: transparency violation
    <statements...>
end

spmd; clear('X'); end

Alternatively, you can free up memory used by a variable by setting its value to empty when it is no longer needed.

parfor ii = 1:4
    <statements...>
    X = [];
    <statements...>
end

In the case of spmd blocks, you can clear its Composite from the client workspace.

In general, the requirement for transparency restricts all dynamic access to variables, because the entire variable might not be present in any given worker. In a transparent workspace, you cannot create, delete, modify, access, or query variables if you do not explicitly specify these variables in the code.

Examples of other actions or functions that violate transparency in a parfor-loop include:

who and whos
evalc, evalin, and assignin with the workspace argument specified as 'caller'
save and load, unless the output of load is assigned to a variable
If a script attempts to read or write variables of the parent workspace, then running this script can cause a transparency violation. To avoid this issue, convert the script to a function, and call it with the necessary variables as input or output arguments.

Note

Transparency applies only to the direct body of the parfor or spmd construct, and not to any functions called from there. The workaround for save and load is to hide the calls to save and load inside a function.

MATLAB does successfully execute eval and evalc statements that appear in functions called from the parfor body.

Parallel Simulink Simulations

You can run Simulink^® models in parallel with the parsim command instead of using parfor-loops. For more information and examples of using Simulink in parallel, see Run Multiple Simulations (Simulink).

If your Simulink model requires access to variables contained in a .mat file, you must load these parameters in the workspace of each worker. You must do this before the parfor-loop, and after opening parpool. To achieve this, you can use spmd or parfevalOnAll, as shown in the examples.
```
spmd 
    evalin('base', 'load(''path/to/file'')') 
end
```
```
parfevalOnAll(@evalin, 0, 'base', 'load(''path/to/file'')')
```
If your model also requires variables defined in the body of your MATLAB script, you must use assignin or evalin to move these variables to the base workspace of each worker, in every parfor iteration.

Documentation