| 1 | //---------------------------------------------------------------------------// |
| 2 | // Copyright (c) 2013-2014 Kyle Lutz <kyle.r.lutz@gmail.com> |
| 3 | // |
| 4 | // Distributed under the Boost Software License, Version 1.0 |
| 5 | // See accompanying file LICENSE_1_0.txt or copy at |
| 6 | // http://www.boost.org/LICENSE_1_0.txt |
| 7 | // |
| 8 | // See http://boostorg.github.com/compute for more information. |
| 9 | //---------------------------------------------------------------------------// |
| 10 | |
| 11 | #include <iostream> |
| 12 | |
| 13 | #include <boost/compute/command_queue.hpp> |
| 14 | #include <boost/compute/kernel.hpp> |
| 15 | #include <boost/compute/program.hpp> |
| 16 | #include <boost/compute/system.hpp> |
| 17 | #include <boost/compute/algorithm/copy.hpp> |
| 18 | #include <boost/compute/container/vector.hpp> |
| 19 | #include <boost/compute/utility/source.hpp> |
| 20 | |
| 21 | namespace compute = boost::compute; |
| 22 | |
| 23 | // this example shows how to use the static c++ kernel language |
| 24 | // extension (currently only supported by AMD) to compile and |
| 25 | // execute a templated c++ kernel. |
| 26 | // Using platform vendor info to decide if this is AMD platform |
| 27 | int main() |
| 28 | { |
| 29 | // get default device and setup context |
| 30 | compute::device device = compute::system::default_device(); |
| 31 | compute::context context(device); |
| 32 | compute::command_queue queue(context, device); |
| 33 | |
| 34 | // check the platform vendor string |
| 35 | if(device.platform().vendor() != "Advanced Micro Devices, Inc." ){ |
| 36 | std::cerr << "error: static C++ kernel language is only " |
| 37 | << "supported on AMD devices." |
| 38 | << std::endl; |
| 39 | return 0; |
| 40 | } |
| 41 | |
| 42 | // create input int values and copy them to the device |
| 43 | int int_data[] = { 1, 2, 3, 4}; |
| 44 | compute::vector<int> int_vector(int_data, int_data + 4, queue); |
| 45 | |
| 46 | // create input float values and copy them to the device |
| 47 | float float_data[] = { 2.0f, 4.0f, 6.0f, 8.0f }; |
| 48 | compute::vector<float> float_vector(float_data, float_data + 4, queue); |
| 49 | |
| 50 | // create kernel source with a templated function and templated kernel |
| 51 | const char source[] = BOOST_COMPUTE_STRINGIZE_SOURCE( |
| 52 | // define our templated function which returns the square of its input |
| 53 | template<typename T> |
| 54 | inline T square(const T x) |
| 55 | { |
| 56 | return x * x; |
| 57 | } |
| 58 | |
| 59 | // define our templated kernel which calls square on each value in data |
| 60 | template<typename T> |
| 61 | __kernel void square_kernel(__global T *data) |
| 62 | { |
| 63 | const uint i = get_global_id(0); |
| 64 | data[i] = square(data[i]); |
| 65 | } |
| 66 | |
| 67 | // explicitly instantiate the square kernel for int's. this allows |
| 68 | // for it to be called from the host with the given mangled name. |
| 69 | template __attribute__((mangled_name(square_kernel_int))) |
| 70 | __kernel void square_kernel(__global int *data); |
| 71 | |
| 72 | // also instantiate the square kernel for float's. |
| 73 | template __attribute__((mangled_name(square_kernel_float))) |
| 74 | __kernel void square_kernel(__global float *data); |
| 75 | ); |
| 76 | |
| 77 | // build the program. must enable the c++ static kernel language |
| 78 | // by passing the "-x clc++" compile option. |
| 79 | compute::program square_program = |
| 80 | compute::program::build_with_source(source, context, "-x clc++" ); |
| 81 | |
| 82 | // create the square kernel for int's by using its mangled name declared |
| 83 | // in the explicit template instantiation. |
| 84 | compute::kernel square_int_kernel(square_program, "square_kernel_int" ); |
| 85 | square_int_kernel.set_arg(0, int_vector); |
| 86 | |
| 87 | // execute the square int kernel |
| 88 | queue.enqueue_1d_range_kernel(kernel: square_int_kernel, global_work_offset: 0, global_work_size: int_vector.size(), local_work_size: 4); |
| 89 | |
| 90 | // print out the squared int values |
| 91 | std::cout << "int's: " ; |
| 92 | compute::copy( |
| 93 | int_vector.begin(), int_vector.end(), |
| 94 | std::ostream_iterator<int>(std::cout, " " ), |
| 95 | queue |
| 96 | ); |
| 97 | std::cout << std::endl; |
| 98 | |
| 99 | // now create the square kernel for float's |
| 100 | compute::kernel square_float_kernel(square_program, "square_kernel_float" ); |
| 101 | square_float_kernel.set_arg(0, float_vector); |
| 102 | |
| 103 | // execute the square int kernel |
| 104 | queue.enqueue_1d_range_kernel(kernel: square_float_kernel, global_work_offset: 0, global_work_size: float_vector.size(), local_work_size: 4); |
| 105 | |
| 106 | // print out the squared float values |
| 107 | std::cout << "float's: " ; |
| 108 | compute::copy( |
| 109 | float_vector.begin(), float_vector.end(), |
| 110 | std::ostream_iterator<float>(std::cout, " " ), |
| 111 | queue |
| 112 | ); |
| 113 | std::cout << std::endl; |
| 114 | |
| 115 | return 0; |
| 116 | } |
| 117 | |