Add runnable GPU main-path prototype

makefile_and_run.py

@@ -9,6 +9,7 @@
 
 
 import AMSS_NCKU_Input as input_data
+import os
 import subprocess
 import time
 
@@ -57,6 +58,48 @@ BUILD_JOBS = 64
 ##################################################################
 
 
+##################################################################
+
+def prepare_gpu_runtime_env():
+    """
+    Create a user-private CUDA MPS environment for GPU runs.
+
+    On shared machines another user's daemon may already occupy the default
+    /tmp/nvidia-mps pipe directory, which makes plain cudaSetDevice/cudaMalloc
+    fail with cudaErrorMpsConnectionFailed.  Binding AMSS-NCKU to a private
+    pipe directory avoids cross-user interference.
+    """
+    env = os.environ.copy()
+
+    pipe_dir = env.get("CUDA_MPS_PIPE_DIRECTORY", f"/tmp/amss-ncku-mps-{os.getuid()}")
+    log_dir  = env.get("CUDA_MPS_LOG_DIRECTORY",  f"/tmp/amss-ncku-mps-log-{os.getuid()}")
+
+    os.makedirs(pipe_dir, exist_ok=True)
+    os.makedirs(log_dir, exist_ok=True)
+
+    env["CUDA_MPS_PIPE_DIRECTORY"] = pipe_dir
+    env["CUDA_MPS_LOG_DIRECTORY"] = log_dir
+
+    control_socket = os.path.join(pipe_dir, "control")
+    if not os.path.exists(control_socket):
+        start = subprocess.run(
+            ["nvidia-cuda-mps-control", "-d"],
+            env=env,
+            stdout=subprocess.DEVNULL,
+            stderr=subprocess.DEVNULL,
+        )
+        if start.returncode != 0:
+            print(f" Warning: failed to start private CUDA MPS daemon in {pipe_dir}")
+        else:
+            print(f" Using private CUDA MPS pipe directory: {pipe_dir}")
+    else:
+        print(f" Using existing private CUDA MPS pipe directory: {pipe_dir}")
+
+    return env
+
+##################################################################
+
+
 
 ##################################################################
 
@@ -146,16 +189,29 @@ def run_ABE():
 
     ## Define the command to run; cast other values to strings as needed
     
+    run_env = None
+
     if (input_data.GPU_Calculation == "no"):
         mpi_command         = NUMACTL_CPU_BIND + " mpirun -np " + str(input_data.MPI_processes) + " ./ABE"
         #mpi_command         = " mpirun -np " + str(input_data.MPI_processes) + " ./ABE"
         mpi_command_outfile = "ABE_out.log"
     elif (input_data.GPU_Calculation == "yes"):
-        mpi_command         = NUMACTL_CPU_BIND + " mpirun -np " + str(input_data.MPI_processes) + " ./ABEGPU"
+        run_env = prepare_gpu_runtime_env()
+        if int(input_data.MPI_processes) == 1:
+            mpi_command = "./ABEGPU"
+        else:
+            mpi_command = NUMACTL_CPU_BIND + " mpirun -np " + str(input_data.MPI_processes) + " ./ABEGPU"
         mpi_command_outfile = "ABEGPU_out.log"
  
     ## Execute the MPI command and stream output
-    mpi_process = subprocess.Popen(mpi_command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, text=True)
+    mpi_process = subprocess.Popen(
+        mpi_command,
+        shell=True,
+        stdout=subprocess.PIPE,
+        stderr=subprocess.STDOUT,
+        text=True,
+        env=run_env,
+    )
 
     ## Write ABE run output to file while printing to stdout
     with open(mpi_command_outfile, 'w') as file0: