General

• What is Thrust?
• Thrust is a C++ template library for CUDA. Thrust allows you to program GPUs using an interface similar the C++ Standard Template Library (STL).
• What is a C++ template library?
• C++ templates are a way to write generic algorithms and data structures. A template library is simply a cohesive collection of such algorithms and data structures in a single package.
• How can I contribute to Thrust?
• There are many ways! Please refer to Contributing for some ideas.
• How do I cite Thrust in papers and other publications?
• Please refer to the page on Citing.
• Do I need to build Thrust?
• No. Since Thrust is a template library you just #include the appropriate header files into your .cu file and compile with nvcc.
• What data structures does Thrust provide?
• Currently Thrust provides thrust::host_vector and thrust::device_vector, which are analogous to std::vector in the STL and reside in the host/device memory. These vector data structures simplify memory management and transferring data between the host and device.
• What algorithms does Thrust provide?
• sorting: thrust::sort and thrust::sort_by_key
• tranformations: thrust::transform
• reductions: thrust::reduce and thrust::transform_reduce
• scans: thrust::inclusive_scan, thrust::exclusive_scan, thrust::transform_inclusive_scan, etc.
• Refer to Documentation for a complete listing
• What version of CUDA do I need to develop applications with Thrust?
• The latest version of Thrust requires CUDA 4.0 or newer.
• What platforms does Thrust support?
• Thrust has been tested extensively on Linux, Windows and MacOSX systems. Refer to the ReleaseChecklist for a complete list.
• When will Thrust support OpenCL?
• The primary barrier to OpenCL support is the lack of an OpenCL compiler and runtime with support for C++ templates (e.g. something similar to nvcc and the CUDA Runtime). These features are necessary to achieve close coupling of the host and device codes.
• Does Thrust depend on any other libraries?
• No, Thrust is self-contained and requires no additional libraries.
• Can I distribute Thrust with my application?
• Yes! Thrust is open-source software released under liberal licensing terms.
• What open-source license does Thrust use?
• Thrust is licensed under the Apache License v2.0
• How do I run the unit tests and performance tests for Thrust?
• Refer to the DeveloperInfo page.

Functionality

• Can I create a thrust::device_vector from memory I've allocated myself?
• No. Instead, wrap your externally allocated raw pointer with thrust::device_ptr and pass it to Thrust algorithms. [example].
• How do I find the array index of the element with the maximum/minumum value?
• Use thrust::max_element() or thrust::min_element(), which are found in the file <thrust/extrema.h> [more info].
• How do I obtain a raw pointer (e.g. int * ptr) from a device_vector?
• Use thrust::raw_pointer_cast(&my_vector[0]) [example].
• Can I call Thrust algorithms inside a CUDA kernel?
• No, it is not currently possible to call Thrust algorithms inside a __global__ or __device__ function.
• Can I call Thrust algorithms from CUDA Fortran?
• Yes! For example, this example shows how to call Thrust's sort algorithm from Fortran.

Troubleshooting

• Make sure you are using CUDA 3.0 or greater (CUDA 4.0 is highly recommended):
• run nvcc --version
• Make sure you're compiling files that #include Thrust with nvcc.
• Make sure that files that #include Thrust have a .cu extension. Other extensions (e.g..cpp) will cause nvcc to treat the file incorrectly and produce an error message.
• If all else fails, send a message to thrust-users and we'll do our best to assist you.