cuda-core

import cuda.core as drv import numpy as np try: # Initialize the CUDA driver API drv.init() # Get device count device_count = drv.cuDeviceGetCount() if device_count == 0: print("No CUDA devices found. Ensure GPU drivers and CUDA Toolkit are installed.") else: print(f"Found {device_count} CUDA device(s).") # Get the first device and create a context device = drv.cuDeviceGet(0) # Flags: 0 for default context creation context = drv.cuCtxCreate(0, device) print(f"Created CUDA context on device 0: {device}") # Prepare host data host_data = np.arange(10, dtype=np.int32) print(f"Host data: {host_data}") # Allocate memory on the device device_ptr = drv.cuMemAlloc(host_data.nbytes) print(f"Allocated {host_data.nbytes} bytes on device at address: {device_ptr}") # Copy host data to device drv.cuMemcpyHtoD(device_ptr, host_data.ctypes.data, host_data.nbytes) print("Copied host data to device.") # Example: Copy device data back to host (optional, for verification) retrieved_data = np.empty_like(host_data) drv.cuMemcpyDtoH(retrieved_data.ctypes.data, device_ptr, retrieved_data.nbytes) print(f"Retrieved data from device: {retrieved_data}") # Clean up: Free device memory and destroy context drv.cuMemFree(device_ptr) drv.cuCtxDestroy(context) print("Successfully freed device memory and destroyed context.") except drv.CUException as e: print(f"CUDA Error: {e}. This often indicates issues with CUDA Toolkit installation, drivers, or device availability.") print("Please ensure you have a compatible NVIDIA GPU, up-to-date drivers, and a correctly installed CUDA Toolkit.") except Exception as e: print(f"An unexpected Python error occurred: {e}")