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Farm works
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@ -17,15 +17,15 @@ let run_sequential f stream =
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let run_parallel_server stream =
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let fetch_result () =
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let fetch_result () : 'a option * int =
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let result, rank, _tag =
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Mpi.receive_status Mpi.any_source Mpi.any_tag Mpi.comm_world
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in
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result, rank
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result, rank
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in
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let send_task client_rank =
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let send_task (client_rank : int) : unit =
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let task =
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try Some (Stream.next stream)
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with Stream.Failure -> None
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@ -34,34 +34,33 @@ let run_parallel_server stream =
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in
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let rec run result_list n_todo =
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let n_todo =
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match Stream.peek stream with
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| None -> n_todo-1
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| _ -> n_todo
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in
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match n_todo with
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| 0 -> result_list
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| _ ->
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let n_todo = ref (Mpi.comm_size Mpi.comm_world ) in
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let f i =
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let rec get_result () =
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begin
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let result, client = fetch_result () in
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let new_result_list =
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match Stream.peek stream with
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| None -> decr n_todo
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| _ -> ()
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end;
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match !n_todo with
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| 0 ->
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begin
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Mpi.barrier Mpi.comm_world;
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None
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end
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| _ ->
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begin
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let result, client = fetch_result () in
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send_task client;
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match result with
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| None -> result_list
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| Some result -> result :: result_list
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in
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send_task client;
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run new_result_list n_todo
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end
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| None -> get_result ()
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| _ -> result
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end
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in
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get_result ()
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in
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let result =
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let n_todo = Mpi.comm_size Mpi.comm_world in
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run [] n_todo
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|> Stream.of_list
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in
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Mpi.barrier Mpi.comm_world;
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result
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Stream.from f
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(** Client side *)
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@ -1,12 +0,0 @@
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(** The Farm skeleton, similar to SklMl.
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The input is a stream of input data, and the output is a stream of data.
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*)
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val run : ('a -> 'b) -> 'a Stream.t -> 'b Stream.t
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(** Run the [worker_function] on every process by popping elements from the
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input stream, and put the results on the output stream. The order of the
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output is consistent with the order of the input. *)
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@ -26,6 +26,8 @@ let () =
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let input = Stream.of_list
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[ (1,2) ; (3,4) ; (5,6) ; (7,8) ; (9,10) ]
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in
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Farm.run f input
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|> Stream.iter (fun (x,y) -> Printf.printf "%d %d\n" x y)
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let stream =
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Farm.run f input
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in
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Stream.iter (fun (x,y) -> Printf.printf "%d %d\n%!" x y) stream
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