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Extend parallel algorithms to work with hpx::partitioned_vector et.al.

Labels: type: enhancement, category: algorithms, category: data-structures, tag: pinned

The existing parallel algorithms should be extended to seamlessly work with distributed data structures like hpx::partitioned_vector. Unfortunately this requires additional code for each specific algorithms.

For more information about the parallel algorithms already implemented see #1141.

Here is the list of algorithms mandated by N4310 which should be ported to the distributed case:

• adjacent_difference (see #2859, #3525)
• adjacent_find (see #2859, #3525)
• all_of any_of none_of (see #2859, #3525)
• copy (see #1346) copy_n
• copy_if
• move (see #2010)
• count count_if (see #1340)
• equal mismatch
• exclusive_scan inclusive_scan (see #2287)
• reduce transform (see #2725)
• fill (#2202)
• fill_n
• find find_if find_if_not (see #2792)
• find_end find_first_of (see #2793)
• for_each
• for_each_n (see #2725)
• generate (see #1968)
• generate_n
• inner_product inplace_merge merge
• is_heap is_heap_until
• is_partitioned is_sorted is_sorted_until
• lexicographical_compare
• max_element min_element minmax_element (#1968)
• partial_sort partial_sort_copy partition partition_copy nth_element sort stable_partition stable_sort
• remove remove_copy remove_copy_if remove_if
• replace replace_copy replace_copy_if replace_if
• reverse reverse_copy
• rotate rotate_copy
• search search_n
• set_difference set_intersection set_symmetric_difference set_union includes
• swap_ranges
• uninitialized_copy uninitialized_copy_n
• uninitialized_fill uninitialized_fill_n
• unique unique_copy

These were added by N4310:

• transform_reduce (see #1333, #2859, #3525)
• transform_exclusive_scan transform_inclusive_scan (see #2725)