I am using cuPy in a python program to perform computations on GPU. My program consists of several functions/classes spread across multiple files. I am using a GPU cluster (NVIDIA V100), consisting of four GPUs. How can I select a particular GPU as the default GPU for the whole program? I found some information at cuPy documentation about use keyword but since there is no example, I am not sure how to utilize it. MWE: maths_ops.py: import cupy as cp class MathsOps: def vector_addition(self, vector1, vector2): return cp.add(vector1, vector2) dummy_class.py: from maths_ops import MathsOps class DummyClass: def __init__(self, maths_ops_instance): self.maths_ops_instance = maths_ops_instance def perform_operation(self, vector1, vector2): result = self.maths_ops_instance.vector_addition(vector1, vector2) return result main.py: from maths_ops import MathsOps from dummy_class import DummyClass # Create an instance of MathsOps maths_ops_instance = MathsOps() # Create an instance of DummyClass with the MathsOps instance dummy_instance = DummyClass(maths_ops_instance) # Example vectors vector1 = cp.array([1, 2, 3]) vector2 = cp.array([4, 5, 6]) # Perform vector addition using DummyClass result = dummy_instance.perform_operation(vector1, vector2) # Print the result print("Vector Addition Result:", result) Question: How do I specify a GPU device (for example, device-1) I'm the main function as the default GPU device that should be used by the program? Continue reading...