Thrust: Code at the speed of light ================================== Thrust is a C++ parallel programming library which resembles the C++ Standard Library. Thrust's **high-level** interface greatly enhances programmer **productivity** while enabling performance portability between GPUs and multicore CPUs. **Interoperability** with established technologies (such as CUDA, TBB, and OpenMP) facilitates integration with existing software. Develop **high-performance** applications rapidly with Thrust! Thrust is included in the NVIDIA HPC SDK and the CUDA Toolkit. Refer to the [Quick Start Guide](http://github.com/thrust/thrust/wiki/Quick-Start-Guide) page for further information and examples. Examples -------- Thrust is best explained through examples. The following source code generates random numbers serially and then transfers them to a parallel device where they are sorted. ```c++ #include #include #include #include #include #include #include int main(void) { // generate 32M random numbers serially thrust::host_vector h_vec(32 << 20); std::generate(h_vec.begin(), h_vec.end(), rand); // transfer data to the device thrust::device_vector d_vec = h_vec; // sort data on the device (846M keys per second on GeForce GTX 480) thrust::sort(d_vec.begin(), d_vec.end()); // transfer data back to host thrust::copy(d_vec.begin(), d_vec.end(), h_vec.begin()); return 0; } ``` This code sample computes the sum of 100 random numbers in parallel: ```c++ #include #include #include #include #include #include #include int main(void) { // generate random data serially thrust::host_vector h_vec(100); std::generate(h_vec.begin(), h_vec.end(), rand); // transfer to device and compute sum thrust::device_vector d_vec = h_vec; int x = thrust::reduce(d_vec.begin(), d_vec.end(), 0, thrust::plus()); return 0; } ``` Releases -------- Thrust is distributed with the NVIDIA HPC SDK and the CUDA Toolkit in addition to GitHub. See the [changelog](CHANGELOG.md) for details about specific releases. | Thrust Release | Included In | | ----------------- | --------------------------------------- | | 1.9.10-1 | NVIDIA HPC SDK 20.7 & CUDA Toolkit 11.1 | | 1.9.10 | NVIDIA HPC SDK 20.5 | | 1.9.9 | CUDA Toolkit 11.0 | | 1.9.8-1 | NVIDIA HPC SDK 20.3 | | 1.9.8 | CUDA Toolkit 11.0 Early Access | | 1.9.7-1 | CUDA Toolkit 10.2 for Tegra | | 1.9.7 | CUDA Toolkit 10.2 | | 1.9.6-1 | NVIDIA HPC SDK 20.3 | | 1.9.6 | CUDA Toolkit 10.1 Update 2 | | 1.9.5 | CUDA Toolkit 10.1 Update 1 | | 1.9.4 | CUDA Toolkit 10.1 | | 1.9.3 | CUDA Toolkit 10.0 | | 1.9.2 | CUDA Toolkit 9.2 | | 1.9.1-2 | CUDA Toolkit 9.1 | | 1.9.0-5 | CUDA Toolkit 9.0 | | 1.8.3 | CUDA Toolkit 8.0 | | 1.8.2 | CUDA Toolkit 7.5 | | 1.8.1 | CUDA Toolkit 7.0 | | 1.8.0 | | | 1.7.2 | CUDA Toolkit 6.5 | | 1.7.1 | CUDA Toolkit 6.0 | | 1.7.0 | CUDA Toolkit 5.5 | | 1.6.0 | | | 1.5.3 | CUDA Toolkit 5.0 | | 1.5.2 | CUDA Toolkit 4.2 | | 1.5.1 | CUDA Toolkit 4.1 | | 1.5.0 | | | 1.4.0 | CUDA Toolkit 4.0 | | 1.3.0 | | | 1.2.1 | | | 1.2.0 | | | 1.1.1 | | | 1.1.0 | | | 1.0.0 | | Adding Thrust To A CMake Project -------------------------------- Since Thrust is a header library, there is no need to build or install Thrust to use it. The `thrust` directory contains a complete, ready-to-use Thrust package upon checkout. We provide CMake configuration files that make it easy to include Thrust from other CMake projects. See the [CMake README](thrust/cmake/README.md) for details. Development Process ------------------- Thrust uses the [CMake build system](https://cmake.org/) to build unit tests, examples, and header tests. To build Thrust as a developer, the following recipe should be followed: ``` # Clone Thrust and CUB repos recursively: git clone --recursive https://github.com/thrust/thrust.git cd thrust # Create build directory: mkdir build cd build # Configure -- use one of the following: cmake .. # Command line interface. ccmake .. # ncurses GUI (Linux only) cmake-gui # Graphical UI, set source/build directories in the app # Build: cmake --build . -j # invokes make (or ninja, etc) # Run tests and examples: ctest ``` By default, a serial `CPP` host system, `CUDA` accelerated device system, and C++14 standard are used. This can be changed in CMake. More information on configuring your Thrust build and creating a pull request can be found in [CONTRIBUTING.md](CONTRIBUTING.md).