Create codistributed array from replicated local data
C = codistributed(X)
C = codistributed(X,codist)
C = codistributed(X,lab,codist)
C = codistributed(C1,codist)
C = codistributed(X)
distributes a replicated
array X
using the default codistributor, creating
a codistributed array C
as
a result. X
must be a replicated array, that is,
it must have the same value on all workers. size(C)
is
the same as size(X)
.
C = codistributed(X,codist)
distributes
a replicated array X
using the distribution scheme
defined by codistributor codist
. X
must
be a replicated array, namely it must have the same value on all workers. size(C)
is
the same as size(X)
. For information on constructing
codistributor objects, see the reference pages for codistributor1d
and codistributor2dbc
.
C = codistributed(X,lab,codist)
distributes
a local array X
that resides on the worker identified
by lab
, using the codistributor codist
.
Local array X
must be defined on all workers, but
only the value from lab
is used to construct C
. size(C)
is
the same as size(X)
.
C = codistributed(C1,codist)
accepts an
array C1
that is already codistributed, and redistributes
it into C
according to the distribution scheme
defined by the codistributor codist
. This is the
same as calling C = redistribute(C1,codist)
. If
the existing distribution scheme for C1
is the
same as that specified in codist
, then the result C
is
the same as the input C1
.
Create a 1000-by-1000 codistributed array C1
using
the default distribution scheme.
spmd N = 1000; X = magic(N); % Replicated on every worker C1 = codistributed(X); % Partitioned among the workers end
Create a 1000-by-1000 codistributed array C2
,
distributed by rows (over its first dimension).
spmd N = 1000; X = magic(N); C2 = codistributed(X,codistributor1d(1)); end
gather
essentially performs
the inverse of codistributed
.
What Is a Datastore? | codistributor1d
| codistributor2dbc
| distributed
| gather
| getLocalPart
| globalIndices
| redistribute
| size
| subsasgn
| subsref