Switch back to Intel toolchain as the default option
Seems that Intel MPI also supports CUDA-aware by setting I_MPI_OFFLOAD to 1. Besides, I_MPI_OFFLOAD_IPC=0 is needed to avoid segfaults.
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@@ -1,7 +1,7 @@
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## Toolchain selection
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## Toolchain selection
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## nvhpc : NVIDIA HPC SDK + CUDA-aware MPI (default)
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## nvhpc : NVIDIA HPC SDK + CUDA-aware MPI (default)
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## intel : Intel oneAPI toolchain (legacy path)
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## intel : Intel oneAPI toolchain (legacy path)
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TOOLCHAIN ?= nvhpc
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TOOLCHAIN ?= intel
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## PGO build mode switch (ABE only; TwoPunctureABE always uses opt flags)
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## PGO build mode switch (ABE only; TwoPunctureABE always uses opt flags)
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## opt : (default) maximum performance with PGO profile-guided optimization
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## opt : (default) maximum performance with PGO profile-guided optimization
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@@ -266,7 +266,7 @@ def run_ABE():
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#mpi_command = " mpirun -np " + str(input_data.MPI_processes) + " ./ABE"
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#mpi_command = " mpirun -np " + str(input_data.MPI_processes) + " ./ABE"
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mpi_command_outfile = "ABE_out.log"
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mpi_command_outfile = "ABE_out.log"
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elif (input_data.GPU_Calculation == "yes"):
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elif (input_data.GPU_Calculation == "yes"):
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mpi_command = NUMACTL_CPU_BIND + " mpirun -np " + str(input_data.MPI_processes) + " ./ABE_CUDA"
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mpi_command = NUMACTL_CPU_BIND + " I_MPI_OFFLOAD=1 I_MPI_OFFLOAD_IPC=0 mpirun -np " + str(input_data.MPI_processes) + " ./ABE_CUDA"
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mpi_command_outfile = "ABEGPU_out.log"
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mpi_command_outfile = "ABEGPU_out.log"
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mpi_env = _gpu_runtime_env()
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mpi_env = _gpu_runtime_env()
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started_mps = _start_cuda_mps_if_requested(mpi_env)
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started_mps = _start_cuda_mps_if_requested(mpi_env)
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