Deprecate SharedArray(T, dims...)

Author: ararslan

base/deprecated.jl

@@ -1685,4 +1685,12 @@ isempty(::Task) = error("isempty not defined for Tasks")
 @deprecate Array{T}(::Type{T}, m::Integer,n::Integer)            Array{T,2}(Int(m),Int(n))
 @deprecate Array{T}(::Type{T}, m::Integer,n::Integer,o::Integer) Array{T,3}(Int(m),Int(n),Int(o))
 
+# Likewise for SharedArrays
+@deprecate SharedArray{T,N}(::Type{T}, dims::Dims{N}; kwargs...) SharedArray{T,N}(dims; kwargs...)
+@deprecate SharedArray{T}(::Type{T}, dims::Int...; kwargs...)    SharedArray{T,length(dims)}(dims...; kwargs...)
+@deprecate(SharedArray{T,N}(filename::AbstractString, ::Type{T}, dims::NTuple{N,Int}, offset; kwargs...),
+           SharedArray{T,N}(filename, dims, offset; kwargs...))
+@deprecate(SharedArray{T}(filename::AbstractString, ::Type{T}, dims::NTuple, offset; kwargs...),
+           SharedArray{T,length(dims)}(filename, dims, offset; kwargs...))
+
 # End deprecations scheduled for 0.6

base/sharedarray.jl

@@ -28,19 +28,8 @@ type SharedArray{T,N} <: DenseArray{T,N}
     end
 end
 
-(::Type{SharedArray{T}}){T,N}(d::NTuple{N,Int}; kwargs...) =
-    SharedArray(T, d; kwargs...)
-(::Type{SharedArray{T}}){T}(d::Integer...; kwargs...) =
-    SharedArray(T, d; kwargs...)
-(::Type{SharedArray{T}}){T}(m::Integer; kwargs...) =
-    SharedArray(T, m; kwargs...)
-(::Type{SharedArray{T}}){T}(m::Integer, n::Integer; kwargs...) =
-    SharedArray(T, m, n; kwargs...)
-(::Type{SharedArray{T}}){T}(m::Integer, n::Integer, o::Integer; kwargs...) =
-    SharedArray(T, m, n, o; kwargs...)
-
 """
-    SharedArray(T::Type, dims::NTuple; init=false, pids=Int[])
+    SharedArray{T,N}(dims::NTuple; init=false, pids=Int[])
 
 Construct a `SharedArray` of a bitstype `T` and size `dims` across the processes specified
 by `pids` - all of which have to be on the same host.
@@ -52,8 +41,39 @@ computation with the master process acting as a driver.
 
 If an `init` function of the type `initfn(S::SharedArray)` is specified, it is called on all
 the participating workers.
+
+    SharedArray{T,N}(filename::AbstractString, dims::NTuple, [offset=0]; mode=nothing, init=false, pids=Int[])
+
+Construct a `SharedArray` backed by the file `filename`, with element
+type `T` (must be a `bitstype`) and size `dims`, across the processes
+specified by `pids` - all of which have to be on the same host. This
+file is mmapped into the host memory, with the following consequences:
+
+- The array data must be represented in binary format (e.g., an ASCII
+  format like CSV cannot be supported)
+
+- Any changes you make to the array values (e.g., `A[3] = 0`) will
+  also change the values on disk
+
+If `pids` is left unspecified, the shared array will be mapped across
+all processes on the current host, including the master. But,
+`localindexes` and `indexpids` will only refer to worker
+processes. This facilitates work distribution code to use workers for
+actual computation with the master process acting as a driver.
+
+`mode` must be one of `"r"`, `"r+"`, `"w+"`, or `"a+"`, and defaults
+to `"r+"` if the file specified by `filename` already exists, or
+`"w+"` if not. If an `init` function of the type
+`initfn(S::SharedArray)` is specified, it is called on all the
+participating workers. You cannot specify an `init` function if the
+file is not writable.
+
+`offset` allows you to skip the specified number of bytes at the
+beginning of the file.
 """
-function SharedArray{T,N}(::Type{T}, dims::Dims{N}; init=false, pids=Int[])
+SharedArray
+
+function (::Type{SharedArray{T,N}}){T,N}(dims::Dims{N}; init=false, pids=Int[])
     isbits(T) || throw(ArgumentError("type of SharedArray elements must be bits types, got $(T)"))
 
     pids, onlocalhost = shared_pids(pids)
@@ -110,39 +130,20 @@ function SharedArray{T,N}(::Type{T}, dims::Dims{N}; init=false, pids=Int[])
     S
 end
 
-SharedArray(T, I::Int...; kwargs...) = SharedArray(T, I; kwargs...)
-
-"""
-    SharedArray(filename::AbstractString, T::Type, dims::NTuple, [offset=0]; mode=nothing, init=false, pids=Int[])
-
-Construct a `SharedArray` backed by the file `filename`, with element
-type `T` (must be a `bitstype`) and size `dims`, across the processes
-specified by `pids` - all of which have to be on the same host. This
-file is mmapped into the host memory, with the following consequences:
-
-- The array data must be represented in binary format (e.g., an ASCII
-  format like CSV cannot be supported)
-
-- Any changes you make to the array values (e.g., `A[3] = 0`) will
-  also change the values on disk
-
-If `pids` is left unspecified, the shared array will be mapped across
-all processes on the current host, including the master. But,
-`localindexes` and `indexpids` will only refer to worker
-processes. This facilitates work distribution code to use workers for
-actual computation with the master process acting as a driver.
-
-`mode` must be one of `"r"`, `"r+"`, `"w+"`, or `"a+"`, and defaults
-to `"r+"` if the file specified by `filename` already exists, or
-`"w+"` if not. If an `init` function of the type
-`initfn(S::SharedArray)` is specified, it is called on all the
-participating workers. You cannot specify an `init` function if the
-file is not writable.
+(::Type{SharedArray{T,N}}){T,N}(I::Integer...; kwargs...) =
+    SharedArray{T,N}(I; kwargs...)
+(::Type{SharedArray{T}}){T}(d::NTuple; kwargs...) =
+    SharedArray{T,length(d)}(d; kwargs...)
+(::Type{SharedArray{T}}){T}(I::Integer...; kwargs...) =
+    SharedArray{T,length(I)}(I; kwargs...)
+(::Type{SharedArray{T}}){T}(m::Integer; kwargs...) =
+    SharedArray{T,1}(m; kwargs...)
+(::Type{SharedArray{T}}){T}(m::Integer, n::Integer; kwargs...) =
+    SharedArray{T,2}(m, n; kwargs...)
+(::Type{SharedArray{T}}){T}(m::Integer, n::Integer, o::Integer; kwargs...) =
+    SharedArray{T,3}(m, n, o; kwargs...)
 
-`offset` allows you to skip the specified number of bytes at the
-beginning of the file.
-"""
-function SharedArray{T,N}(filename::AbstractString, ::Type{T}, dims::NTuple{N,Int},
+function (::Type{SharedArray{T,N}}){T,N}(filename::AbstractString, dims::NTuple{N,Int},
         offset::Integer=0; mode=nothing, init=false, pids::Vector{Int}=Int[])
     if !isabspath(filename)
         throw(ArgumentError("$filename is not an absolute path; try abspath(filename)?"))
@@ -208,6 +209,10 @@ function SharedArray{T,N}(filename::AbstractString, ::Type{T}, dims::NTuple{N,In
     S
 end
 
+(::Type{SharedArray{T}}){T,N}(filename::AbstractString, dims::NTuple{N,Int}, offset::Integer=0;
+                              mode=nothing, init=false, pids::Vector{Int}=Int[]) =
+    SharedArray{T,N}(filename, dims, offset; mode=mode, init=init, pids=pids)
+
 function initialize_shared_array(S, onlocalhost, init, pids)
     if onlocalhost
         init_loc_flds(S)
@@ -246,6 +251,7 @@ typealias SharedMatrix{T} SharedArray{T,2}
 
 length(S::SharedArray) = prod(S.dims)
 size(S::SharedArray) = S.dims
+ndims(S::SharedArray) = length(S.dims)
 linearindexing{S<:SharedArray}(::Type{S}) = LinearFast()
 
 function reshape{T,N}(a::SharedArray{T}, dims::NTuple{N,Int})
@@ -307,21 +313,21 @@ localindexes(S::SharedArray) = S.pidx > 0 ? range_1dim(S, S.pidx) : 1:0
 unsafe_convert{T}(::Type{Ptr{T}}, S::SharedArray) = unsafe_convert(Ptr{T}, sdata(S))
 
 function convert(::Type{SharedArray}, A::Array)
-    S = SharedArray(eltype(A), size(A))
+    S = SharedArray{eltype(A),ndims(A)}(size(A))
     copy!(S, A)
 end
 function convert{T}(::Type{SharedArray{T}}, A::Array)
-    S = SharedArray(T, size(A))
+    S = SharedArray{T,ndims(A)}(size(A))
     copy!(S, A)
 end
 function convert{TS,TA,N}(::Type{SharedArray{TS,N}}, A::Array{TA,N})
-    S = SharedArray(TS, size(A))
+    S = SharedArray{TS,ndims(A)}(size(A))
     copy!(S, A)
 end
 
 function deepcopy_internal(S::SharedArray, stackdict::ObjectIdDict)
     haskey(stackdict, S) && return stackdict[S]
-    R = SharedArray(eltype(S), size(S); pids = S.pids)
+    R = SharedArray{eltype(S),ndims(S)}(size(S); pids = S.pids)
     copy!(sdata(R), sdata(S))
     stackdict[S] = R
     return R
@@ -468,16 +474,16 @@ end
 
 # convenience constructors
 function shmem_fill(v, dims; kwargs...)
-    SharedArray(typeof(v), dims; init = S->fill!(S.loc_subarr_1d, v), kwargs...)
+    SharedArray{typeof(v),length(dims)}(dims; init = S->fill!(S.loc_subarr_1d, v), kwargs...)
 end
 shmem_fill(v, I::Int...; kwargs...) = shmem_fill(v, I; kwargs...)
 
 # rand variant with range
 function shmem_rand(TR::Union{DataType, UnitRange}, dims; kwargs...)
     if isa(TR, UnitRange)
-        SharedArray(Int, dims; init = S -> map!(x -> rand(TR), S.loc_subarr_1d, S.loc_subarr_1d), kwargs...)
+        SharedArray{Int,length(dims)}(dims; init = S -> map!(x -> rand(TR), S.loc_subarr_1d, S.loc_subarr_1d), kwargs...)
     else
-        SharedArray(TR, dims; init = S -> map!(x -> rand(TR), S.loc_subarr_1d, S.loc_subarr_1d), kwargs...)
+        SharedArray{TR,length(dims)}(dims; init = S -> map!(x -> rand(TR), S.loc_subarr_1d, S.loc_subarr_1d), kwargs...)
     end
 end
 shmem_rand(TR::Union{DataType, UnitRange}, i::Int; kwargs...) = shmem_rand(TR, (i,); kwargs...)
@@ -487,7 +493,7 @@ shmem_rand(dims; kwargs...) = shmem_rand(Float64, dims; kwargs...)
 shmem_rand(I::Int...; kwargs...) = shmem_rand(I; kwargs...)
 
 function shmem_randn(dims; kwargs...)
-    SharedArray(Float64, dims; init = S-> map!(x -> randn(), S.loc_subarr_1d, S.loc_subarr_1d), kwargs...)
+    SharedArray{Float64,length(dims)}(dims; init = S-> map!(x -> randn(), S.loc_subarr_1d, S.loc_subarr_1d), kwargs...)
 end
 shmem_randn(I::Int...; kwargs...) = shmem_randn(I; kwargs...)
 

doc/src/manual/parallel-computing.md

@@ -312,7 +312,7 @@ Parallel for loops like these must be avoided. Fortunately, [Shared Arrays](@ref
 to get around this limitation:
 
 ```julia
-a = SharedArray(Float64,10)
+a = SharedArray{Float64}(10)
 @parallel for i=1:10
   a[i] = i
 end
@@ -720,10 +720,10 @@ just returns the object itself, so it's safe to use [`sdata()`](@ref) on any `Ar
 The constructor for a shared array is of the form:
 
 ```julia
-SharedArray(T::Type, dims::NTuple; init=false, pids=Int[])
+SharedArray{T,N}(dims::NTuple; init=false, pids=Int[])
 ```
 
-which creates a shared array of a bits type `T` and size `dims` across the processes specified
+which creates an `N`-dimensional shared array of a bits type `T` and size `dims` across the processes specified
 by `pids`.  Unlike distributed arrays, a shared array is accessible only from those participating
 workers specified by the `pids` named argument (and the creating process too, if it is on the
 same host).
@@ -741,7 +741,7 @@ julia> addprocs(3)
  3
  4
 
-julia> S = SharedArray(Int, (3,4), init = S -> S[Base.localindexes(S)] = myid())
+julia> S = SharedArray{Int,2}((3,4), init = S -> S[Base.localindexes(S)] = myid())
 3×4 SharedArray{Int64,2}:
  2  2  3  4
  2  3  3  4
@@ -762,7 +762,7 @@ convenient for splitting up tasks among processes. You can, of course, divide th
 you wish:
 
 ```julia
-julia> S = SharedArray(Int, (3,4), init = S -> S[indexpids(S):length(procs(S)):length(S)] = myid())
+julia> S = SharedArray{Int,2}((3,4), init = S -> S[indexpids(S):length(procs(S)):length(S)] = myid())
 3×4 SharedArray{Int64,2}:
  2  2  2  2
  3  3  3  3
@@ -861,8 +861,8 @@ end
 If we create `SharedArray`s and time these functions, we get the following results (with `julia -p 4`):
 
 ```julia
-q = SharedArray(Float64, (500,500,500))
-u = SharedArray(Float64, (500,500,500))
+q = SharedArray{Float64,3}((500,500,500))
+u = SharedArray{Float64,3}((500,500,500))
 
 # Run once to JIT-compile
 advection_serial!(q, u)

test/parallel_exec.jl

@@ -231,11 +231,11 @@ test_indexing(RemoteChannel(id_other))
 dims = (20,20,20)
 
 if is_linux()
-    S = SharedArray(Int64, dims)
+    S = SharedArray{Int64,3}(dims)
     @test startswith(S.segname, "/jl")
     @test !ispath("/dev/shm" * S.segname)
 
-    S = SharedArray(Int64, dims; pids=[id_other])
+    S = SharedArray{Int64,3}(dims; pids=[id_other])
     @test startswith(S.segname, "/jl")
     @test !ispath("/dev/shm" * S.segname)
 end
@@ -298,7 +298,7 @@ copy!(s, sdata(d))
 a = rand(dims)
 @test sdata(a) == a
 
-d = SharedArray(Int, dims, init = D->fill!(D.loc_subarr_1d, myid()))
+d = SharedArray{Int}(dims, init = D->fill!(D.loc_subarr_1d, myid()))
 for p in procs(d)
     idxes_in_p = remotecall_fetch(p, d) do D
         parentindexes(D.loc_subarr_1d)[1]
@@ -309,7 +309,7 @@ for p in procs(d)
     @test d[idxl] == p
 end
 
-d = @inferred(SharedArray(Float64, (2,3)))
+d = @inferred(SharedArray{Float64,2}((2,3)))
 @test isa(d[:,2], Vector{Float64})
 
 ### SharedArrays from a file
@@ -320,7 +320,7 @@ write(fn, 1:30)
 sz = (6,5)
 Atrue = reshape(1:30, sz)
 
-S = @inferred(SharedArray(fn, Int, sz))
+S = @inferred(SharedArray{Int,2}(fn, sz))
 @test S == Atrue
 @test length(procs(S)) > 1
 @sync begin
@@ -338,14 +338,14 @@ read!(fn, filedata)
 finalize(S)
 
 # Error for write-only files
-@test_throws ArgumentError SharedArray(fn, Int, sz, mode="w")
+@test_throws ArgumentError SharedArray{Int,2}(fn, sz, mode="w")
 
 # Error for file doesn't exist, but not allowed to create
-@test_throws ArgumentError SharedArray(joinpath(tempdir(),randstring()), Int, sz, mode="r")
+@test_throws ArgumentError SharedArray{Int,2}(joinpath(tempdir(),randstring()), sz, mode="r")
 
 # Creating a new file
 fn2 = tempname()
-S = SharedArray(fn2, Int, sz, init=D->D[localindexes(D)] = myid())
+S = SharedArray{Int,2}(fn2, sz, init=D->D[localindexes(D)] = myid())
 @test S == filedata
 filedata2 = similar(Atrue)
 read!(fn2, filedata2)
@@ -355,7 +355,7 @@ finalize(S)
 # Appending to a file
 fn3 = tempname()
 write(fn3, ones(UInt8, 4))
-S = SharedArray(fn3, UInt8, sz, 4, mode="a+", init=D->D[localindexes(D)]=0x02)
+S = SharedArray{UInt8}(fn3, sz, 4, mode="a+", init=D->D[localindexes(D)]=0x02)
 len = prod(sz)+4
 @test filesize(fn3) == len
 filedata = Array{UInt8}(len)
@@ -438,7 +438,7 @@ A = @inferred(convert(SharedArray, AA))
 B = @inferred(convert(SharedArray, AA'))
 @test B*A == ctranspose(AA)*AA
 
-d=SharedArray(Int64, (10,10); init = D->fill!(D.loc_subarr_1d, myid()), pids=[id_me, id_other])
+d=SharedArray{Int64,2}((10,10); init = D->fill!(D.loc_subarr_1d, myid()), pids=[id_me, id_other])
 d2 = map(x->1, d)
 @test reduce(+, d2) == 100
 
@@ -459,12 +459,12 @@ map!(x->1, d, d)
 # Shared arrays of singleton immutables
 @everywhere immutable ShmemFoo end
 for T in [Void, ShmemFoo]
-    s = @inferred(SharedArray(T, 10))
+    s = @inferred(SharedArray{T}(10))
     @test T() === remotecall_fetch(x->x[3], workers()[1], s)
 end
 
 # Issue #14664
-d = SharedArray(Int,10)
+d = SharedArray{Int}(10)
 @sync @parallel for i=1:10
     d[i] = i
 end
@@ -474,8 +474,8 @@ for (x,i) in enumerate(d)
 end
 
 # complex
-sd = SharedArray(Int,10)
-se = SharedArray(Int,10)
+sd = SharedArray{Int}(10)
+se = SharedArray{Int}(10)
 @sync @parallel for i=1:10
     sd[i] = i
     se[i] = i
@@ -498,7 +498,7 @@ for id in [id_me, id_other]
     finalize_and_test((r=RemoteChannel(id); put!(r, 1); r))
 end
 
-d = SharedArray(Int,10)
+d = SharedArray{Int}(10)
 finalize(d)
 @test_throws BoundsError d[1]