Refactor computation logic for cluster processing

Author: decarvalhojunior-fh

README.md

@@ -36,15 +36,17 @@ cid4 = addcluster(<IP4>, 64; access_node_args = <A4>, compute_node_args = <C4>)
 @everywhere workers() reduce1(x) = @spawnat role = :worker 1 reduce0(x)
 
 # run the computation logic at each computing process
-@everywhere cids @everywhere workers() begin
-    MPI.Init()
-    size = MPI.Comm_size(MPI.COMM_WORLD)
-    rank = MPI.Comm_rank(MPI.COMM_WORLD)
-    @info "my info: rank=$rank, size=$size, cluster=$clusterid"
-    X = rand(1:10)
-    r = MPI.Reduce(X, (x, y) -> x + y, 0, MPI.COMM_WORLD)
-    rank == 0 && @spawnat role = :worker 1 reduce1(r)
-    MPI.Finalize()
+for cid in clusters()
+    @cluster_everywhere cid begin
+       MPI.Init()
+       size = MPI.Comm_size(MPI.COMM_WORLD)
+       rank = MPI.Comm_rank(MPI.COMM_WORLD)
+       @info "my info: rank=$rank, size=$size, cluster=$clusterid"
+       X = rand(1:10)
+       r = MPI.Reduce(X, (x, y) -> x + y, 0, MPI.COMM_WORLD)
+       rank == 0 && @spawnat role = :worker 1 reduce1(r)
+       MPI.Finalize()
+    end
 end
 
 @info "The sum across all clusters is $(SUM[])"