边界检查

和许多其他现代编程语言一样，Julia 在访问数组元素的时候也要通过边界检查来确保程序安全。当循环次数很多，或者在其他性能敏感的场景下，你可能希望不进行边界检查以提高运行时性能。比如要使用矢量 (SIMD) 指令，循环体就不能有分支语句，因此无法进行边界检查。Julia 提供了一个宏 @inbounds(...) 来告诉编译器在指定语句块不进行边界检查。用户自定义的数组类型可以通过宏 @boundscheck(...) 来达到上下文敏感的代码选择目的。

移除边界检查

宏 @boundscheck(...) 把代码块标记为要执行边界检查。但当这些代码块被被宏 @inbounds(...) 标记的代码包裹时，它们可能会被编译器移除。仅当@boundscheck(...) 代码块被调用函数包裹时，编译器会移除它们。比如你可能这样写的 sum 方法：

function sum(A::AbstractArray)
    r = zero(eltype(A))
    for i in eachindex(A)
        @inbounds r += A[i]
    end
    return r
end

使用自定义的类数组类型 MyArray，我们有：

@inline getindex(A::MyArray, i::Real) = (@boundscheck checkbounds(A,i); A.data[to_index(i)])

当 getindex 被 sum 包裹时，对 checkbounds(A,i) 的调用会被忽略。如果存在多层包裹，最多只有一个 @boundscheck 被忽略。这个规则用来防止将来代码被改变时潜在的多余忽略。

Propagating inbounds

There may be certain scenarios where for code-organization reasons you want more than one layer between the @inbounds and @boundscheck declarations. For instance, the default getindex methods have the chain getindex(A::AbstractArray, i::Real) calls getindex(IndexStyle(A), A, i) calls _getindex(::IndexLinear, A, i).

To override the "one layer of inlining" rule, a function may be marked with Base.@propagate_inbounds to propagate an inbounds context (or out of bounds context) through one additional layer of inlining.

The bounds checking call hierarchy

The overall hierarchy is:

• checkbounds(A, I...) which calls

  • checkbounds(Bool, A, I...) which calls

    • checkbounds_indices(Bool, axes(A), I) which recursively calls

      • checkindex for each dimension

Here A is the array, and I contains the "requested" indices. axes(A) returns a tuple of "permitted" indices of A.

checkbounds(A, I...) throws an error if the indices are invalid, whereas checkbounds(Bool, A, I...) returns false in that circumstance. checkbounds_indices discards any information about the array other than its axes tuple, and performs a pure indices-vs-indices comparison: this allows relatively few compiled methods to serve a huge variety of array types. Indices are specified as tuples, and are usually compared in a 1-1 fashion with individual dimensions handled by calling another important function, checkindex: typically,

checkbounds_indices(Bool, (IA1, IA...), (I1, I...)) = checkindex(Bool, IA1, I1) &
                                                      checkbounds_indices(Bool, IA, I)

so checkindex checks a single dimension. All of these functions, including the unexported checkbounds_indices have docstrings accessible with ? .

If you have to customize bounds checking for a specific array type, you should specialize checkbounds(Bool, A, I...). However, in most cases you should be able to rely on checkbounds_indices as long as you supply useful axes for your array type.

If you have novel index types, first consider specializing checkindex, which handles a single index for a particular dimension of an array. If you have a custom multidimensional index type (similar to CartesianIndex), then you may have to consider specializing checkbounds_indices.

Note this hierarchy has been designed to reduce the likelihood of method ambiguities. We try to make checkbounds the place to specialize on array type, and try to avoid specializations on index types; conversely, checkindex is intended to be specialized only on index type (especially, the last argument).

Emit bounds checks

Julia can be launched with --check-bounds={yes|no|auto} to emit bounds checks always, never, or respect @inbounds declarations.