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Legacy Documentation

Mathematica 8 (2010)

This is documentation for Mathematica 8, which was
based on an earlier version of Wolfram Language.
View current documentation (Version 14.3)

SetSharedFunction

SetSharedFunction
declares the symbols as shared functions whose downvalues are synchronized among all parallel kernels.
  • Downvalues for a shared function defined on any kernel are maintained by the master kernel and every access on a parallel subkernel is synchronized through the master kernel.
  • Expressions of the form that would remain unevaluated give Null .
(1)
Make fs be a (global) shared function:
Each subkernel makes a definition for the same shared variable:
Without sharing, each subkernel has its own (local) copy of the function:
Make fs be a (global) shared function:
Each subkernel makes a definition for the same shared variable:
Out[2]=
Out[3]=
Without sharing, each subkernel has its own (local) copy of the function:
Out[4]=
Out[5]=
(4)
Define and share a function:
When called from each subkernel, the function updates next on the master kernel:
Set up a shared function with a default rule:
Make additional definitions on the subkernels:
Since the function is shared, the master kernel knows about the additional rules:
Maintain indexed shared variables with a default value:
Define a shared function to manipulate the local variable results on the master kernel:
Call the function from the subkernels:
The variable on the master has been modified:
(1)
A delayed definition for a shared function made on the master kernel:
Such definitions are always evaluated on the master kernel, whichever kernel evaluates it:
A definition for a shared function made on one of the parallel kernels:
Such definitions are always evaluated on the kernel that asks for the value:
(3)
Shared functions can be used for synchronization:
Less efficient is the use of a shared variable and critical section:
A constructor for a simple queue data type:
Create two shared queues:
Fill the input queue:
Work on the elements of the input queue in parallel and put results into the output queue:
Use a single shared function to communicate both input and result:
Set up a search and display its progress until it is manually aborted:
The results found so far—a list of the number of factors of :
(3)
A shared function is inefficient for mere code distribution and leads to sequential evaluation:
Simply distribute the definitions of any function needed on the parallel kernels:
Separate read and write operations on a shared variable are not thread-safe:
Use a shared function to synchronize access to an (unshared) variable:
Alternatively, use CriticalSection to make a whole code section atomic:
Parallel dynamic programming:
(1)
A parallel version of Sow :
New in 7


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