Merge pull request #102 from JuliaParallel/eschnett/montecarlo

Rename Monte Carlo implementation back to `montecarlo.jl`

Author: eschnett

examples/07-pi-impl.jl

@@ -7,7 +7,7 @@ like to use, subject to  X-1 being an even divisor
 of 1e6, e.g., set X=5.
 =#
 
-include("07-pi-impl.jl")
+include("montecarlo.jl")
 
 function pi_wrapper()
     4.0 * (norm(rand(2)) < 1)
@@ -24,10 +24,13 @@ end
 
 # do the monte carlo: 10^6 reps of single draws
 function main()
-    reps = 10^7 # desired number of MC reps
-    nreturns = 1
-    pooled = 10^5
-    montecarlo(pi_wrapper, pi_monitor, reps, nreturns, pooled)
+    MPI.Init()
+    n_evals = 10^7 # desired number of MC reps
+    n_returns = 1
+    batchsize = 10^5
+    montecarlo(pi_wrapper, pi_monitor,
+               MPI.COMM_WORLD, n_evals, n_returns, batchsize)
+    MPI.Finalize()
 end
 
 main()

examples/07-pi.jl renamed to examples/07-pi-montecarlo.jl

@@ -0,0 +1,57 @@
+import MPI
+
+function montecarlo(mc_eval::Function, mc_monitor::Function,
+                    comm::MPI.Comm, # MPI communicator
+                    n_evals::Integer, # total number of evaluations
+                    n_returns::Integer, # number of return values per evaluation
+                    batchsize::Integer=1) # transmission size
+    rank = MPI.Comm_rank(comm)
+    commsize = MPI.Comm_size(comm)
+
+    # bookkeeping
+    if mod(n_evals, commsize-1) != 0
+        if rank == 0
+            println("Error (montecarlo):")
+            println("    n_evals=$n_evals, commsize=$commsize")
+            println("Choose commsize so that n_evals/(commsize-1) is integer")
+        end
+        MPI.Finalize()
+        exit(1)
+    end
+    n_pernode = div(n_evals, commsize-1)
+
+    # number of evaluations per worker
+    if mod(n_pernode, batchsize) != 0
+        batchsize = div(n_pernode, commsize-1)
+    end
+    if mod(n_pernode, batchsize) != 0
+        if rank == 0
+            println("Error (montecarlo):")
+            println("    n_pernode=$n_pernode, batchsize=$batchsize")
+            println("Choose commsize so that n_pernode/batchsize is integer")
+        end
+        MPI.Finalize()
+        exit(1)
+    end
+
+    if rank > 0
+        # workers
+        contrib = zeros(batchsize, n_returns)
+        @inbounds for i = 1:div(n_pernode, batchsize)
+            # do work
+            for j = 1:batchsize
+                contrib[j,:] = mc_eval()
+            end
+            MPI.Send(contrib, 0, 0, comm)
+        end
+    else
+        # manager
+        results = zeros(n_evals, n_returns)
+        contrib = zeros(batchsize, n_returns)
+        for nresults = 1:div(n_evals, batchsize)
+            MPI.Recv!(contrib, MPI.ANY_SOURCE, 0, comm)
+            results[nresults*batchsize-batchsize+1:nresults*batchsize,:] = contrib
+            mc_monitor(nresults*batchsize, results)
+        end
+    end
+end