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K = globalIndices(R, dim)
K
= globalIndices(R, dim, lab)
[E,F] = globalIndices(R, dim)
[E,F]
= globalIndices(R, dim, lab)
K = codist.globalIndices(dim, lab)
[E,F] = codist.globalIndices(dim, lab)
globalIndices tell you the relationship between indices on a local part and the corresponding index range in a given dimension on the distributed array. The globalIndices method on a codistributor object allows you to get this relationship without actually creating the array.
K = globalIndices(R, dim) or K = globalIndices(R, dim, lab) returns a vector K so that getLocalPart(R) = R(...,K,...) in the specified dimension dim on the specified lab. If the lab argument is omitted, the default is labindex.
[E,F] = globalIndices(R, dim) or [E,F] = globalIndices(R, dim, lab) returns two integers E and F so that getLocalPart(R) = R(...,E:F,...) in the specified dimension dim on the specified lab. If the lab argument is omitted, the default is labindex.
K = codist.globalIndices(dim, lab) is the same as K = globalIndices(R, dim, lab), where codist is the codistributor for R, or codist = getCodistributor(R). This allows you to get the global indices for a codistributed array without having to create the array itself.
[E,F] = codist.globalIndices(dim, lab) is the same as [E,F] = globalIndices(R, dim, lab), where codist is the codistributor for R, or codist = getCodistributor(R). This allows you to get the global indices for a codistributed array without having to create the array itself.
Create a 2-by-22 codistributed array among four labs, and view the global indices on each lab:
spmd
D = codistributed.zeros(2, 22, codistributor1d(2,[6 6 5 5]));
if labindex == 1
K = globalIndices(D, 2); % returns K = 1:6.
elseif labindex == 2
[E,F] = globalIndices(D, 2); % returns E = 7, F = 12.
end
K = globalIndices(D, 2, 3); % returns K = 13:17.
[E,F] = globalIndices(D, 2, 4); % returns E = 18, F = 22.
endUse globalIndices to load data from a file and construct a codistributed array distributed along its columns, i.e., dimension 2. Notice how globalIndices makes the code not specific to the number of labs and alleviates you from calculating offsets or partitions.
spmd
siz = [1000, 1000];
codistr = codistributor1d(2, [], siz);
% Use globalIndices to figure out which columns
% each lab should load.
[firstCol, lastCol] = codistr.globalIndices(2);
% Call user-defined function readRectangleFromFile to
% load all the values that should go into
% the local part for this lab.
labLocalPart = readRectangleFromFile(fileName, ...
1, siz(1), firstCol, lastCol);
% With the local part and codistributor,
% construct the corresponding codistributed array.
D = codistributed.build(labLocalPart, codistr);
end ![]() | getLocalPart | gop | ![]() |

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