Update docstring

Author: andrewjradcliffe

src/vfindminmax.jl

@@ -31,13 +31,13 @@ vfindminmax(f, op, init, A, dims::Int) = vfindminmax(f, op, init, A, (dims,))
 
 Return the value and the index of the argument which maximizes `f` over the
 dimensions `dims`, which may be `::Int`, `::NTuple{M, Int} where {M}` or `::Colon`.
-Expands upon the functionality provided in Julia Base.
+Expands upon the functionality provided in Julia (v1.8) Base.
 
 # Additional Notes
 Due to the current limitations of LoopVectorization, searches over the first dimension
 of an array are not well-supported. A workaround is possible by reshaping `A` but
 the resultant performance is often only on par with `findmax`. As a temporary convenience,
-`findmax1` is provided for explicit uses of the re-shaping strategy, though the user
+`vfindmax1` is provided for explicit uses of the re-shaping strategy, though the user
 is cautioned as to the performance problems.
 
 # Warning
@@ -50,13 +50,13 @@ vfindmax(f::F, A, dims) where {F<:Function} = vfindminmax(f, >, typemin, A, dims
 
 Return the value and the index of the argument which minimizes `f` over the
 dimensions `dims`, which may be `::Int`, `::NTuple{M, Int} where {M}` or `::Colon`.
-Expands upon the functionality provided in Julia Base.
+Expands upon the functionality provided in Julia (v1.8) Base.
 
 # Additional Notes
 Due to the current limitations of LoopVectorization, searches over the first dimension
 of an array are not well-supported. A workaround is possible by reshaping `A` but
 the resultant performance is often only on par with `findmin`. As a temporary convenience,
-`findmin1` is provided for explicit uses of the re-shaping strategy, though the user
+`vfindmin1` is provided for explicit uses of the re-shaping strategy, though the user
 is cautioned as to the performance problems.
 
 # Warning