JuliaParallel / JuliaParallel/DistributedArrays.jl
localindices methods in conflict with SharedArrays
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It seems like there is a conflict between localindices method between SharedArrays and DistributedArrays. Please, see the REPL output below.
10:46:39 $ julia-1.0
_
_ _ _(_)_ | Documentation: https://docs.julialang.org
(_) | (_) (_) |
_ _ _| |_ __ _ | Type "?" for help, "]?" for Pkg help.
| | | | | | |/ _` | |
| | |_| | | | (_| | | Version 1.0.2 (2018-11-08)
_/ |\__'_|_|_|\__'_| | Official https://julialang.org/ release
|__/ |
julia> using SharedArrays
julia> SharedArrays.
SharedArray include range_1dim shm_unlink
SharedMatrix indexpids sa_refs shmem_fill
SharedVector init_loc_flds sdata shmem_rand
_shm_mmap_array initialize_shared_array shared_pids shmem_randn
eval localindices shm_mmap_array sub_1dim
finalize_refs print_shmem_limits shm_open
julia> using DistributedArrays
WARNING: using DistributedArrays.localindices in module Main conflicts with an existing identifier.
help?> SharedArrays.localindices
localindices(S::SharedArray)
Returns a range describing the "default" indices to be handled by the current process. This range should
be interpreted in the sense of linear indexing, i.e., as a sub-range of 1:length(S). In multi-process
contexts, returns an empty range in the parent process (or any process for which indexpids returns 0).
It's worth emphasizing that localindices exists purely as a convenience, and you can partition work on the
array among workers any way you wish. For a SharedArray, all indices should be equally fast for each
worker process.
help?> DistributedArrays.localindices
localindices(d)
A tuple describing the indices owned by the local process. Returns a tuple with empty ranges if no local
part exists on the calling process.
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