Add optim test

Project.toml

@@ -11,7 +11,8 @@ julia = "1.6"
 MPI = "0.20"
 
 [extras]
+Optim = "429524aa-4258-5aef-a3af-852621145aeb"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Test"]
+test = ["Optim", "Test"]

test/runtests.jl

@@ -6,8 +6,9 @@ ENV["JULIA_PROJECT"] = dirname(Base.active_project())
 JQM = JobQueueMPI
 
 @testset verbose = true "JobQueueMPI Tests" begin
-    mpiexec(exe -> run(`$exe -n 3 $(Base.julia_cmd()) --project test_1.jl`))
-    mpiexec(exe -> run(`$exe -n 3 $(Base.julia_cmd()) --project test_2.jl`))
-    mpiexec(exe -> run(`$exe -n 3 $(Base.julia_cmd()) --project test_pmap_mpi.jl`))
+    run(`$(mpiexec()) -n 3 $(Base.julia_cmd()) --project test_1.jl`)
+    run(`$(mpiexec()) -n 3 $(Base.julia_cmd()) --project test_2.jl`)
+    run(`$(mpiexec()) -n 3 $(Base.julia_cmd()) --project test_pmap_mpi.jl`)
+    run(`$(mpiexec()) -n 3 $(Base.julia_cmd()) --project test_pmap_mpi_optim.jl`)
     include("test_pmap_serial.jl")
 end

test/test_pmap_mpi_optim.jl

@@ -0,0 +1,52 @@
+import JobQueueMPI as JQM
+using Test
+using MPI
+using Optim
+
+JQM.mpi_init()
+
+N = 5
+data = collect(1:N)
+function g(x, i, data)
+    return i * (x[i] - 2 * i) ^ 2 + data[i]
+end
+x0 = zeros(N)
+list_i = collect(1:N)
+fake_input = Int[] # ignored
+
+
+let
+    is_done = false
+    if JQM.is_controller_process()
+        ret = optimize(x0, NelderMead()) do x
+            MPI.bcast(is_done, MPI.COMM_WORLD)
+            g_x = JQM.pmap((v)->g(v[1], v[2], data), [(x, i) for i in list_i])
+            return sum(g_x)
+        end
+        # tell workers to stop calling pmap
+        is_done = true
+        MPI.bcast(is_done, MPI.COMM_WORLD)
+        @testset "pmap MPI Optim" begin
+            @test maximum(Optim.minimizer(ret) .- collect(2:2:2N)) ≈ 0.0 atol = 1e-3
+            @test Optim.minimum(ret) ≈ sum(1:N) atol = 1e-3
+        end
+    else
+        # optimize will call pmap multiple times
+        # hence, the other processes need to be continuously calling pmap
+        # to work with the controller.
+        # once the controller leaves the optimize function it will
+        # broadcast a is_done = true, so that the workers stop the
+        # infinite loop of pmaps.
+        while true
+            is_done = MPI.bcast(is_done, MPI.COMM_WORLD)
+            if is_done
+                break
+            end
+            JQM.pmap((v)->g(v[1], v[2], data), fake_input)
+        end
+    end
+end
+
+JQM.mpi_barrier()
+
+JQM.mpi_finalize()