rename @parallel to @distributed. part of #19578 (#25528)

Author: JeffBezanson

docs/src/index.md

@@ -41,7 +41,7 @@ Distributed.@fetch
 Distributed.@fetchfrom
 Distributed.@async
 Distributed.@sync
-Distributed.@parallel
+Distributed.@distributed
 Distributed.@everywhere
 Distributed.clear!(::Any, ::Any; ::Any)
 Distributed.remoteref_id

src/Distributed.jl

@@ -26,7 +26,7 @@ export
     @fetch,
     @fetchfrom,
     @everywhere,
-    @parallel,
+    @distributed,
 
     AbstractWorkerPool,
     addprocs,
@@ -78,6 +78,8 @@ include("pmap.jl")
 include("managers.jl")    # LocalManager and SSHManager
 include("precompile.jl")
 
+@eval @deprecate $(Symbol("@parallel")) $(Symbol("@distributed"))
+
 function _require_callback(mod::Symbol)
     if Base.toplevel_load[] && myid() == 1 && nprocs() > 1
         # broadcast top-level import/using from node 1 (only)

src/macros.jl

@@ -279,38 +279,38 @@ function make_pfor_body(var, body)
 end
 
 """
-    @parallel
+    @distributed
 
-A parallel for loop of the form :
+A distributed memory, parallel for loop of the form :
 
-    @parallel [reducer] for var = range
+    @distributed [reducer] for var = range
         body
     end
 
 The specified range is partitioned and locally executed across all workers. In case an
-optional reducer function is specified, `@parallel` performs local reductions on each worker
+optional reducer function is specified, `@distributed` performs local reductions on each worker
 with a final reduction on the calling process.
 
-Note that without a reducer function, `@parallel` executes asynchronously, i.e. it spawns
+Note that without a reducer function, `@distributed` executes asynchronously, i.e. it spawns
 independent tasks on all available workers and returns immediately without waiting for
 completion. To wait for completion, prefix the call with [`@sync`](@ref), like :
 
-    @sync @parallel for var = range
+    @sync @distributed for var = range
         body
     end
 """
-macro parallel(args...)
+macro distributed(args...)
     na = length(args)
     if na==1
         loop = args[1]
     elseif na==2
         reducer = args[1]
         loop = args[2]
     else
-        throw(ArgumentError("wrong number of arguments to @parallel"))
+        throw(ArgumentError("wrong number of arguments to @distributed"))
     end
     if !isa(loop,Expr) || loop.head !== :for
-        error("malformed @parallel loop")
+        error("malformed @distributed loop")
     end
     var = loop.args[1].args[1]
     r = loop.args[1].args[2]

test/distributed_exec.jl

@@ -11,7 +11,7 @@ include(joinpath(Sys.BINDIR, "..", "share", "julia", "test", "testenv.jl"))
 # Test a few "remote" invocations when no workers are present
 @test remote(myid)() == 1
 @test pmap(identity, 1:100) == [1:100...]
-@test 100 == @parallel (+) for i in 1:100
+@test 100 == @distributed (+) for i in 1:100
         1
     end
 
@@ -272,14 +272,14 @@ end
 test_regular_io_ser(Future())
 test_regular_io_ser(RemoteChannel())
 
-# Test @parallel load balancing - all processors should get either M or M+1
+# Test @distributed load balancing - all processors should get either M or M+1
 # iterations out of the loop range for some M.
-ids = @parallel((a,b)->[a;b], for i=1:7; myid(); end)
+ids = @distributed((a,b)->[a;b], for i=1:7; myid(); end)
 workloads = Int[sum(ids .== i) for i in 2:nprocs()]
 @test maximum(workloads) - minimum(workloads) <= 1
 
-# @parallel reduction should work even with very short ranges
-@test @parallel(+, for i=1:2; i; end) == 3
+# @distributed reduction should work even with very short ranges
+@test @distributed(+, for i=1:2; i; end) == 3
 
 @test_throws ArgumentError sleep(-1)
 @test_throws ArgumentError timedwait(()->false, 0.1, pollint=-0.5)
@@ -698,7 +698,7 @@ end
 
 # issue #8207
 let A = Any[]
-    @parallel (+) for i in (push!(A,1); 1:2)
+    @distributed (+) for i in (push!(A,1); 1:2)
         i
     end
     @test length(A) == 1
@@ -817,13 +817,13 @@ end
 
 # issue #16451
 rng=RandomDevice()
-retval = @parallel (+) for _ in 1:10
+retval = @distributed (+) for _ in 1:10
     rand(rng)
 end
 @test retval > 0.0 && retval < 10.0
 
 rand(rng)
-retval = @parallel (+) for _ in 1:10
+retval = @distributed (+) for _ in 1:10
     rand(rng)
 end
 @test retval > 0.0 && retval < 10.0
@@ -1267,7 +1267,7 @@ foreach(wait, refs)
 #6760
 if true
     a = 2
-    x = @parallel (vcat) for k=1:2
+    x = @distributed (vcat) for k=1:2
         sin(a)
     end
 end