Matrix Types¶

Draft Specification
Decisions for the Implementation in Clang

Clang provides a C/C++ language extension that allows users to directly express fixed-size 2-dimensional matrices as language values and perform arithmetic on them.

This feature is currently experimental, and both its design and its implementation are in flux.

A matrix type is a scalar type with an underlying element type, a constant number of rows, and a constant number of columns. Matrix types with the same element type, rows, and columns are the same type. A value of a matrix type includes storage for rows * columns values of the element type. The internal layout, overall size and alignment are implementation-defined.

The maximum of the product of the number of rows and columns is implementation-defined. If that implementation-defined limit is exceeded, the program is ill-formed.

Currently, the element type of a matrix is only permitted to be one of the following types:

an integer type (as in C2x 6.2.5p19), but excluding enumerated types and _Bool
the standard floating types float or double
a half-precision floating point type, if one is supported on the target

Other types may be supported in the future.

Matrix Type Attribute ¶

Matrix types can be declared by adding the matrix_type attribute to the declaration of a typedef (or a C++ alias declaration). The underlying type of the typedef must be a valid matrix element type. The attribute takes two arguments, both of which must be integer constant expressions that evaluate to a value greater than zero. The first specifies the number of rows, and the second specifies the number of columns. The underlying type of the typedef becomes a matrix type with the given dimensions and an element type of the former underlying type.

If a declaration of a typedef-name has a matrix_type attribute, then all declaration of that typedef-name shall have a matrix_type attribute with the same element type, number of rows, and number of columns.

Standard Conversions ¶

The standard conversions are extended as follows. Note that these conversions are intentionally not listed as satisfying the constraints for assignment, which is to say, they are only permitted as explicit casts, not as implicit conversions.

A value of matrix type can be converted to another matrix type if the number of rows and columns are the same and the value’s elements can be converted to the element type of the result type. The result is a matrix where each element is the converted corresponding element.

A value of any real type (as in C2x 6.2.5p17) can be converted to a matrix type if it can be converted to the element type of the matrix. The result is a matrix where all elements are the converted original value.

If the number of rows or columns differ between the original and resulting type, the program is ill-formed.

Arithmetic Conversions ¶

The usual arithmetic conversions are extended as follows.

Insert at the start:

If both operands are of matrix type, no arithmetic conversion is performed.
If one operand is of matrix type and the other operand is of a real type, convert the real type operand to the matrix type according to the standard conversion rules.

Matrix Type Element Access Operator ¶

An expression of the form E1 [E2] [E3], where E1 has matrix type cv M, is a matrix element access expression. Let T be the element type of M, and let R and C be the number of rows and columns in M respectively. The index expressions shall have integral or unscoped enumeration type and shall not be uses of the comma operator unless parenthesized. The first index expression shall evaluate to a non-negative value less than R, and the second index expression shall evaluate to a non-negative value less than C, or else the expression has undefined behavior. If E1 is a prvalue, the result is a prvalue with type T and is the value of the element at the given row and column in the matrix. Otherwise, the result is a glvalue with type cv T and with the same value category as E1 which refers to the element at the given row and column in the matrix.

Programs containing a single subscript expression into a matrix are ill-formed.

Note: We considered providing an expression of the form postfix-expression [expression] to access columns of a matrix. We think that such an expression would be problematic once both column and row major matrixes are supported: depending on the memory layout, either accessing columns or rows can be done efficiently, but not both. Instead, we propose to provide builtins to extract rows and columns from a matrix. This makes the operations more explicit.

Matrix Type Binary Operators ¶

Each matrix type supports the following binary operators: +, - and *. The * operator provides matrix multiplication, while + and - are performed element-wise. There are also scalar versions of the operators, which take a matrix type and the matrix element type. The operation is applied to all elements of the matrix using the scalar value.

For BIN_OP in +, -, * given the expression M1 BIN_OP M2 where at least one of M1 or M2 is of matrix type and, for *, the other is of a real type:

The usual arithmetic conversions are applied to M1 and M2. [ Note: if M1 or M2 are of a real type, they are broadcast to matrices here. — end note ]
M1 and M2 shall be of the same matrix type.
The result is equivalent to Res in the following where col is the number of columns and row is the number of rows in the matrix type:

decltype(M1) Res;
for (int C = 0; C < col; ++C)
  for (int R = 0; R < row; ++R)
    Res[R][C] = M1[R][C] BIN_OP M2[R][C];

Given the expression M1 * M2 where M1 and M2 are of matrix type:

The usual arithmetic conversions are applied to M1 and M2.
The type of M1 shall have the same number of columns as the type of M2 has rows. The element types of M1 and M2 shall be the same type.
The resulting type, MTy, is a matrix type with the common element type, the number of rows of M1 and the number of columns of M2.
The result is equivalent to Res in the following where EltTy is the element type of MTy, col is the number of columns, row is the number of rows in MTy and inner is the number of columns of M1:

MTy Res;
for (int C = 0; C < col; ++C) {
  for (int R = 0; R < row; ++R) {
    EltTy Elt = 0;
    for (int K = 0; K < inner; ++K) {
      Elt += M1[R][K] * M2[K][C];
  }
  Res[R][C] = Elt;
}

All operations on matrix types match the behavior of the element type with respect to signed overflows.

With respect to floating-point contraction, rounding and environment rules, operations on matrix types match the behavior of the elementwise operations in the corresponding expansions provided above.

Operations on floating-point matrices have the same rounding and floating-point environment behavior as ordinary floating-point operations in the expression’s context. For the purposes of floating-point contraction, all calculations done as part of a matrix operation are considered intermediate operations, and their results need not be rounded to the format of the element type until the final result in the containing expression. This is subject to the normal restrictions on contraction, such as #pragma STDC FP_CONTRACT.

For the +=, -= and *= operators the semantics match their expanded variants.

Matrix Type Builtin Operations ¶

Each matrix type supports a collection of builtin expressions that look like function calls but do not form an overload set. Here they are described as function declarations with rules for how to construct the argument list types and return type and the library description elements from [library.description.structure.specifications]/3 in the C++ standard.

Definitions:

M, M1, M2, M3 - Matrix types
T - Element type
row, col - Row and column arguments respectively.

M2 __builtin_matrix_transpose(M1 matrix)

Remarks: The return type is a cv-unqualified matrix type that has the same element type as M1 and has the the same number of rows as M1 has columns and the same number of columns as M1 has rows.

Returns: A matrix Res equivalent to the code below, where col refers to the number of columns of M, and row to the number of rows of M.

Effects: Equivalent to:

M Res;
for (int C = 0; C < col; ++C)
  for (int R = 0; R < row; ++R)
    Res[C][R] = matrix[R][C];

M __builtin_matrix_column_major_load(T *ptr, size_t row, size_t col, size_t columnStride)

Mandates: row and col shall be integral constants greater than 0.

Preconditions: columnStride is greater than or equal to row.

Remarks: The return type is a cv-unqualified matrix type with an element type of the cv-unqualified version of T and a number of rows and columns equal to row and col respectively. The parameter columnStride is optional and if omitted row is used as columnStride.

Returns: A matrix Res equivalent to:

M Res;
for (size_t C = 0; C < col; ++C) {
  for (size_t R = 0; R < row; ++K)
    Res[R][C] = ptr[R];
  ptr += columnStride
}

void __builtin_matrix_column_major_store(M matrix, T *ptr, size_t columnStride)

Preconditions: columnStride is greater than or equal to the number of rows in M.

Remarks: The type T is the const-unqualified version of the matrix argument’s element type. The parameter columnStride is optional and if omitted, the number of rows of M is used as columnStride.

Effects: Equivalent to:

for (size_t C = 0; C < columns in M; ++C) {
  for (size_t R = 0; R < rows in M; ++K)
    ptr[R] = matrix[R][C];
  ptr += columnStride
}

TODOs ¶

TODO: Does it make sense to allow M::element_type, M::rows, and M::columns where M is a matrix type? We don’t support this anywhere else, but it’s convenient. The alternative is using template deduction to extract this information. Also add spelling for C.

Future Work: Initialization syntax.

Decisions for the Implementation in Clang ¶

This section details decisions taken for the implementation in Clang and is not part of the draft specification.

The elements of a value of a matrix type are laid out in column-major order without padding.

We propose to provide a Clang option to override this behavior and allow contraction of those operations (e.g. -ffp-contract=matrix).

TODO: Specify how matrix values are passed to functions.

Clang 12 documentation

Matrix Types