Build parallel.pool.Constant from data or function handle
C = parallel.pool.Constant(X)
C = parallel.pool.Constant(FH)
C = parallel.pool.Constant(FH,CLEANUP)
C = parallel.pool.Constant(COMP)
C = parallel.pool.Constant(X)
copies the
value X
to each worker and returns a parallel.pool.Constant
object, C
, which allows each worker to access the
value X
within a parallel language construct (parfor
, spmd
, parfeval
)
using the property C.Value
. This can improve performance
when you have multiple parfor-loops accessing the same constant set
of data, because X
is transferred only once to
the workers.
C = parallel.pool.Constant(FH)
evaluates
function handle FH
on each worker and stores the
result in C.Value
. This is also useful for creating
and using any handle-type resources on the workers, such as file handles
and database connections.
C = parallel.pool.Constant(FH,CLEANUP)
evaluates
function handle FH
on each worker and stores the
result in C.Value
. When C
is
cleared, the function handle CLEANUP
is evaluated
with a single argument C.Value
on each worker.
C = parallel.pool.Constant(COMP)
uses the
values stored in the Composite COMP
, and stores
them in C.Value
on each worker. This is especially
useful when the data that you need to use inside a parfor-loop can
be constructed only on the workers, such as when the data is too large
to conveniently fit in the client, or when it is being loaded from
a file that only the workers can access. If COMP
does
not have a defined value on every worker, an error results.
parallel.pool.Constant
must be called in
the MATLAB client session.
parallel.pool.Constant
automatically starts
a parallel pool, if possible. If no pool is running, and one cannot
be started automatically, parallel.pool.Constant
generates
an error.
This example shows how to create a numeric parallel.pool.Constant,
and use it in multiple parfor
-loops on the same
pool.
First, create some large data on the client, then build a parallel.pool.Constant, transferring the data to the pool only once.
data = rand(1000); c = parallel.pool.Constant(data); for ii = 1:10 % Run multiple PARFOR loops accessing the data. parfor jj = 1:10 x(ii,jj) = c.Value(ii,jj); end end
This examples shows how to create a parallel.pool.Constant with a function handle and a cleanup function.
Create a temporary file on each worker. By passing @fclose
as
the second argument, the file is automatically closed when c
goes
out of scope.
c = parallel.pool.Constant(@() fopen(tempname(pwd),'wt'),@fclose); spmd disp(fopen(c.Value)); % Displays the temporary filenames. end parfor idx = 1:1000 fprintf(c.Value,'Iteration: %d\n',idx); end clear c; % Closes the temporary files.
This example shows how to build large data sets as a Composite
on pool workers inside an spmd
block, and then
use that data as a parallel.pool.Constant inside a parfor
-loop.
spmd if labindex == 1 x = labBroadcast(1,rand(5000)); else x = labBroadcast(1); end end xc = parallel.pool.Constant(x); parfor idx = 1:10 s(idx) = sum(xc.Value(:,idx)); end s
s = 1.0e+03 * 2.5108 2.5031 2.5123 2.4909 2.4957 2.5462 2.4859 2.5320 2.5076 2.5432
parcluster
| parfeval
| parfor
| parpool
| spmd