// Copyright (c) 2020-2025 Advanced Micro Devices, Inc. All rights reserved. // // Permission is hereby granted, free of charge, to any person obtaining a copy // of this software and associated documentation files (the "Software"), to deal // in the Software without restriction, including without limitation the rights // to use, copy, modify, merge, publish, distribute, sublicense, and/or sell // copies of the Software, and to permit persons to whom the Software is // furnished to do so, subject to the following conditions: // // The above copyright notice and this permission notice shall be included in all // copies or substantial portions of the Software. // // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR // IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, // FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE // AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER // LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, // OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE // SOFTWARE. #include #include // If you create a global `thrust::device_vector` with the default allocator, // you'll get an error during program termination when the memory of the vector // is freed, as the CUDA runtime cannot be used during program termination. // // To get around this, you can create your own allocator which ignores // deallocation failures that occur because the CUDA runtime is shut down. extern "C" cudaError_t cudaFreeIgnoreShutdown(void* ptr) { cudaError_t const err = cudaFree(ptr); if (cudaSuccess == err || cudaErrorCudartUnloading == err) { return cudaSuccess; } return err; } using device_ignore_shutdown_memory_resource = thrust::system::cuda::detail::cuda_memory_resource>; template using device_ignore_shutdown_allocator = thrust::mr::stateless_resource_allocator>; thrust::device_vector> d; int main() { d.resize(25); }