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Hi Michael,
You are right ifyou have N columns in your matrix A, thenLDA=N for row-major case.
In general leading dimension is equal to the number of elements in major dimension.Also it isequal to the distance in elements between two neighbor elements in a line of minor dimension.
Thusif you have no extra elements in your matrix with M rows and N columns, then:
- In row-major case: row ilays in memory right after row i-1and thus LDA=N - number of elements in row.
- In column-major case: column ilays in memory right after column i-1and thus LDA=M - number of elements in column.
If you refer to a submatrix ( m x n )then you use as leading dimension the number of elements in major dimension of the whole matrix (as above)whilem andn in subroutine's inputparametersdescribes the size of the submatrix.
You are welcome.
Alexander.
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Hi Michael,
You are right ifyou have N columns in your matrix A, thenLDA=N for row-major case.
In general leading dimension is equal to the number of elements in major dimension.Also it isequal to the distance in elements between two neighbor elements in a line of minor dimension.
Thusif you have no extra elements in your matrix with M rows and N columns, then:
- In row-major case: row ilays in memory right after row i-1and thus LDA=N - number of elements in row.
- In column-major case: column ilays in memory right after column i-1and thus LDA=M - number of elements in column.
If you refer to a submatrix ( m x n )then you use as leading dimension the number of elements in major dimension of the whole matrix (as above)whilem andn in subroutine's inputparametersdescribes the size of the submatrix.
You are welcome.
Alexander.
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