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In computing, rowmajor order and columnmajor order are methods for storing multidimensional arrays in linear storage such as random access memory.
The difference between the orders lies in which elements of an array are contiguous in memory. In a rowmajor order, the consecutive elements of a row reside next to each other, whereas the same holds true for consecutive elements of a column in a columnmajor order. While the terms allude to the rows and columns of a twodimensional array, i.e. a matrix, the orders can be generalized to arrays of any dimension by noting that the terms rowmajor and columnmajor are equivalent to lexicographic and colexicographic orders, respectively.
Data layout is critical for correctly passing arrays between programs written in different programming languages. It is also important for performance when traversing an array because modern CPUs process sequential data more efficiently than nonsequential data. This is primarily due to CPU caching. In addition, contiguous access makes it possible to use SIMD instructions that operate on vectors of data. In some media such as tape or NAND flash memory, accessing sequentially is orders of magnitude faster than nonsequential access.^{[citation needed]}
The terms rowmajor and columnmajor stem from the terminology related to grouping objects. A general way to order objects with many attributes is to first group and order them by one attribute, and then, within each such group, group and order them by another attribute, etc. If more than one attribute participate in ordering, the first would be called major and the last minor. If two attributes participate in ordering, it is sufficient to name only the major attribute.
In the case of arrays, the attributes are the indices along each dimension. For matrices in mathematical notation, the first index indicates the row, and the second indicates the column, e.g., given a matrix A , a_{1,2} is in its first row and second column. This convention is carried over to the syntax in programming languages,^{[1]} although often with indexes starting at 0 instead of 1.^{[2]}
Even though the row is indicated by the first index and the column by the second index, no grouping order between the dimensions is implied yet. We can then choose to group and order the indices either rowmajor or columnmajor. The terminology can be applied to even higher dimensional arrays. Rowmajor grouping starts from the leftmost index and columnmajor from the rightmost index, leading to lexicographic and colexicographics orders, respectively.
For example, for the array
The two possible ways are:


Note how the use of A[i][j]
with multistep indexing as in C, as opposed to a neutral notation like A(i,j)
as in Fortran, almost inevitably implies rowmajor order for syntactic reasons, so to say, because it can be rewritten as (A[i])[j]
, and the A[i]
row part can even be assigned to an intermediate variable that is then indexed in a separate expression. (No other implications should be assumed, e.g., Fortran is not columnmajor simply because of its notation, and even the above implication could intentionally be circumvented in a new language.)
To use columnmajor order in a rowmajor environment, or vice versa, for whatever reason, one workaround could be to assign nonconventional roles to the indexes (using the first index for the column and the second index for the row), and another could be to bypass language syntax by explicitly computing positions in a onedimensional array. Of course, deviating from convention probably incurs a cost that increases with the degree of necessary interaction with conventional language features and other code, not only in the form of increased vulnerability to mistakes (forgetting to also invert matrix multiplication order, reverting to convention during code maintenance, etc.), but also in the form of having to actively rearrange elements which has to be weighed against any original purpose of increasing performance.
Programming languages or their standard libraries that support multidimensional arrays typically have a native rowmajor or columnmajor storage order for these arrays.
Rowmajor order is used in C/C++/ObjectiveC (for Cstyle arrays), PL/I,^{[3]} Pascal,^{[4]} Speakeasy,^{[citation needed]} SAS,^{[5]} and Rasdaman.^{[6]}
Columnmajor order is used in Fortran, MATLAB,^{[7]} GNU Octave, SPlus,^{[8]} R,^{[9]} Julia,^{[10]} and Scilab.^{[11]}
A special case would be OpenGL (and OpenGL ES) for graphics processing. Since "recent mathematical treatments of linear algebra and related fields invariably treat vectors as columns," designer Mark Segal decided to substitute this for the convention in predecessor IRIS GL, which was to write vectors as rows; for compatibility, transformation matrices would still be stored in vectormajor rather than coordinatemajor order, and he then used the "subterfuge [to] say that matrices in OpenGL are stored in column major order".^{[12]} This was really only relevant for presentation, because matrix multiplication was stackbased and could still be interpreted as postmultiplication, but, worse, reality leaked through the Cbased API because individual elements would be accessed as M[vector][coordinate]
or, effectively, M[column][row]
, which unfortunately muddled the convention that the designer sought to adopt, and this was even preserved in the OpenGL Shading Language that was later added (although this also makes it possible to access coordinates by name instead, e.g., M[vector].y
). As a result, many developers will now simply declare that having the column as the first index is the definition of columnmajor, even though this is clearly not the case with a real columnmajor language like Fortran.
A typical alternative for dense array storage is to use Iliffe vectors, which typically store elements in the same row contiguously (like rowmajor order), but not the rows themselves. They are used in (ordered by age): Java,^{[13]} C#/CLI/.Net, Scala,^{[14]} and Swift.
Even less dense is to use lists of lists, e.g., in Python,^{[15]} and in the Wolfram Language of Wolfram Mathematica.^{[16]}
An alternative approach uses tables of tables, e.g., in Lua.^{[17]}
Support for multidimensional arrays may also be provided by external libraries, which may even support arbitrary orderings, where each dimension has a stride value, and rowmajor or columnmajor are just two possible resulting interpretations.
Rowmajor order is the default in NumPy^{[18]} (for Python).
Columnmajor order is the default in Eigen^{[19]} (for C++).
Torch (for Lua) changed from columnmajor^{[20]} to rowmajor^{[21]} default order.
As exchanging the indices of an array is the essence of array transposition, an array stored as rowmajor but read as columnmajor (or vice versa) will appear transposed. As actually performing this rearrangement in memory is typically an expensive operation, some systems provide options to specify individual matrices as being stored transposed. The programmer must then decide whether or not to rearrange the elements in memory, based on the actual usage (including the number of times that the array is reused in a computation).
For example, the Basic Linear Algebra Subprograms functions are passed flags indicating which arrays are transposed.^{[22]}
The concept generalizes to arrays with more than two dimensions.
For a ddimensional array with dimensions N_{k} (k=1...d), a given element of this array is specified by a tuple of d (zerobased) indices .
In rowmajor order, the last dimension is contiguous, so that the memoryoffset of this element is given by:
In columnmajor order, the first dimension is contiguous, so that the memoryoffset of this element is given by:
where the empty product is the multiplicative identity element, i.e., .
For a given order, the stride in dimension k is given by the multiplication value in parentheses before index n_{k} in the right handside summations above.
More generally, there are d! possible orders for a given array, one for each permutation of dimensions (with rowmajor and columnorder just 2 special cases), although the lists of stride values are not necessarily permutations of each other, e.g., in the 2by3 example above, the strides are (3,1) for rowmajor and (1,2) for columnmajor.
Initial values specified for an array are assigned to successive elements of the array in rowmajor order (final subscript varying most rapidly).
An arraytype that specifies a sequence of two or more indextypes shall be an abbreviated notation for an arraytype specified to have as its indextype the first indextype in the sequence and to have a componenttype that is an arraytype specifying the sequence of indextypes without the first indextype in the sequence and specifying the same componenttype as the original specification.
From right to left, the rightmost dimension represents columns; the next dimension represents rows. [...] SAS places variables into a multidimensional array by filling all rows in order, beginning at the upper left corner of the array (known as rowmajor order).
Because Scilab stores arrays in column major format, the elements of a column are adjacent (i.e. a separation of 1) in linear format.
If the storage order is not specified, then Eigen defaults to storing the entry in columnmajor.