--- David Abrahams <dave@boost-consulting.com> wrote:
"Ralf W. Grosse-Kunstleve" <rwgk@yahoo.com> writes:
--- David Abrahams <dave@boost-consulting.com> wrote:
with expression templates, and of course, zero abstraction penalty ;-)
Is a reference-counted array type also part of the plan?
Not specifically. We'll probably be relying on Boost.Move (in the sandbox) to avoid unneccessary copies. We may use reference-counting to implement an "fine-grained immutable" array type, but if so, that will provide a complete illusion of value semantics and *not* reference semantics. It's crucial that
array a = b; a *= 2;
never alters b. A concept taxonomy in which b is sometimes altered and sometimes not would be impossible to write generic code for.
You are hitting the nail on the head. Experience with my own reference-counted array type tells me that the issue of immutability/constness needs extreme care. My own solution has the glaring shortcoming of not providing a const-reference-counted array type (excuses available on request :-). But having said that, I found it a lot worse not to be able to write a function that returns a new array without incurring a deep copy. Move semantics in one form or another is absolutely crucial to enable writing of readable code. Some related thoughts from an amateur array library designer that may or may not be useful: 0. The two fundamental properties of array types are: - Memory management model - Indexing model 1. I found the following memory management models for arrays to be essential in practical applications (i.e. I implemented them all, and make heavy use of all): stack, fixed size stack, variable size, fixed capacity heap, variable capacity, one owner (e.g. std::vector) heap, variable capacity, shared ownership reference to any of these (i.e. "no management") 2. Common "indexing models" are 1-dim indexing (e.g. std::vector), 2-dim (matrix types), n-dim regular grids (e.g. Fortran's DIMENSION statement, Python's Numeric arrays, Blitz). However, these are just typical examples. Applications often require custom indexing models (e.g. we have periodic grids and grids with other types of symmetry; spare matrices may be viewed as another example). 3. A general purpose array library should provide a mechanism for reusing memory management models and indexing models in various combinations. This could lead to: memory_model<typename ValueType, typename IndexingModelType> or indexing_model<typename ValueType, typename MemoryModelType> 4. Array algebras (unary and binary operators, functions) are a third property that is ideally separated from memory models and, if applicable, indexing models. This could lead to: template < typename ValueType, typename MemoryModelType, typename IndexingModelType, typename AlgebraType> array; In an ideal world I could then do this: template <typename ValueType, std::size_t MaxSize> typedef array< ValueType, stack_variable<MaxSize>, matrix_indexing, matrix_algebra> small_matrix; small_matrix<double, 20> a(3,3), b(4,5); template <typename ValueType> typedef array< ValueType, heap_shared, matrix_indexing, matrix_algebra> shared_matrix; shared_matrix<double> a(300, 400); template <typename ValueType, std::size_t NDim> typedef array< ValueType, heap_shared, c_convention<NDim>, // or fortran_convention<NDim> element_wise_algebra> n_dim_c_array; n_dim_c_array<double, 3> a(10,20,30); [I know we don't have template typedefs :-( :-( ] 5. Expression templates are an optimization on top of all this and in my practical experience the least important of all the points mentioned here. In all likelihood the 5-10% of code that matter for runtime performance have to be hand-optimized anyway, usually leading to distortions of the original, intuitive code beyond recognition. Having or not having to throw in a few extra loops by hand doesn't make a difference. Ralf __________________________________ Do you Yahoo!? Yahoo! Mail - You care about security. So do we. http://promotions.yahoo.com/new_mail