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							- # StarPU --- Runtime system for heterogeneous multicore architectures.
 
- #
 
- # Copyright (C) 2020       Université de Bordeaux, CNRS (LaBRI UMR 5800), Inria
 
- #
 
- # StarPU is free software; you can redistribute it and/or modify
 
- # it under the terms of the GNU Lesser General Public License as published by
 
- # the Free Software Foundation; either version 2.1 of the License, or (at
 
- # your option) any later version.
 
- #
 
- # StarPU is distributed in the hope that it will be useful, but
 
- # WITHOUT ANY WARRANTY; without even the implied warranty of
 
- # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
 
- #
 
- # See the GNU Lesser General Public License in COPYING.LGPL for more details.
 
- #
 
- using StarPU
 
- @target STARPU_CPU
 
- @codelet function codeletA() :: Nothing
 
-     # print("[Task A] Value = ", val[]);
 
-     # do nothing
 
- end
 
- @target STARPU_CPU
 
- @codelet function codeletB(val ::Ref{Int32}) :: Nothing
 
-     # println("[Task B] Value = ", val[]);
 
-     val[] = val[] *2
 
- end
 
- function callbackB(task)
 
-     sleep(1)
 
-     starpu_task_end_dep_release(task)
 
- end
 
- @target STARPU_CPU
 
- @codelet function codeletC(val ::Ref{Int32}) :: Nothing
 
-     # println("[Task C] Value = ", val[]);
 
-     val[] = val[] *2
 
- end
 
- function callbackC(task)
 
-     starpu_task_end_dep_release(task)
 
- end
 
- function main()
 
-     value = Ref(Int32(12))
 
-     @starpu_block let
 
-         perfmodel = starpu_perfmodel(
 
-             perf_type = starpu_perfmodel_type(STARPU_HISTORY_BASED),
 
-             symbol = "history_perf"
 
-         )
 
-         clA = starpu_codelet(
 
-             cpu_func = "codeletA",
 
-             perfmodel = perfmodel
 
-         )
 
-         clB = starpu_codelet(
 
-             cpu_func = "codeletB",
 
-             modes = [STARPU_RW],
 
-             perfmodel = perfmodel
 
-         )
 
-         clC = starpu_codelet(
 
-             cpu_func = "codeletC",
 
-             modes = [STARPU_RW],
 
-             perfmodel = perfmodel
 
-         )
 
-         handle = starpu_data_register(value)
 
- 	starpu_data_set_sequential_consistency_flag(handle, 0)
 
-         taskA = starpu_task(cl = clA, detach=0)
 
-         taskB = starpu_task(cl = clB, handles = [handle], callback=callbackB, callback_arg=taskA)
 
- 	taskC = starpu_task(cl = clC, handles = [handle], callback=callbackC, callback_arg=taskA)
 
- 	starpu_task_end_dep_add(taskA, 2)
 
-         starpu_task_declare_deps(taskC, taskB)
 
-         starpu_task_submit(taskA)
 
-         starpu_task_submit(taskB)
 
-         starpu_task_submit(taskC)
 
-         starpu_task_wait(taskA)
 
-         starpu_data_acquire_on_node(handle, STARPU_MAIN_RAM, STARPU_R);
 
- 	# Waiting for taskA should have also waited for taskB and taskC
 
-         if value[] != 48
 
-             error("Incorrect value $(value[]) (expected 48)")
 
-         end
 
- 	starpu_data_release_on_node(handle, STARPU_MAIN_RAM);
 
-     end
 
-     println("Value = ", value[])
 
- end
 
- # Disable garbage collector because of random segfault/hang when using mutex.
 
- # This issue should be solved with Julia release 1.5.
 
- GC.enable(false)
 
- starpu_init()
 
- main()
 
- starpu_shutdown()
 
- GC.enable(true)
 
 
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