cublasDestroy

cublasDestroy is a routine provided by NVIDIA’s CUDA Basic Linear Algebra Subroutines (cuBLAS) library. It is used to release resources allocated for a cuBLAS handle. The cuBLAS API is a GPU‑accelerated version of the standard BLAS interface, and a handle is created with cublasCreate before any matrix operations can be performed. When the user no longer needs the handle, cublasDestroy must be called to free device memory, release internal data structures, and decrement reference counts that may otherwise lead to resource leaks.

The declaration of the function in the cuBLAS header files is standard:

cublasStatus_t cublasDestroy(cublasHandle_t handle);

The parameter ‘handle’ is the cuBLAS handle obtained from cublasCreate. The function returns a value of type cublasStatus_t indicating success or failure. On success, CUBLAS_STATUS_SUCCESS is returned. Typical failure codes include CUBLAS_STATUS_NOT_INITIALIZED if the library was not initialized, CUBLAS_STATUS_ALLOC_FAILED if internal allocation failed, or CUBLAS_STATUS_INVALID_VALUE if an invalid argument is passed. The function implicitly calls cudaDeviceReset for the default CUDA context, which also destroys all associated memory and objects unless a non‑default context is used.

Preferred usage pattern: After finishing all cuBLAS operations, the program should invoke cublasDestroy(handle). This is typically placed just before the program terminates or before a new handle is created. Skipping cublasDestroy may leave CUDA memory allocated until the process exits, which in long‑running applications can cause significant memory overhead.

Because cuBLAS handles are not reusable after destruction, a fresh call to cublasCreate is necessary to obtain a usable handle for subsequent calls. The function is thread‑safe; each handle is thread‑specific and can be used in parallel streams, with synchronization handled either explicitly by the programmer or implicitly by stream execution order.

In summary, cublasDestroy is the deconstruction function for cuBLAS handles, responsible for proper cleanup of GPU resources and preventing memory leaks in CUDA applications.