Tag: OpenCL

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ASIN ‏ : ‎ B00HL2GODM
Publisher ‏ : ‎ Packt Publishing (December 23, 2013)
Publication date ‏ : ‎ December 23, 2013
Language ‏ : ‎ English
File size ‏ : ‎ 8187 KB
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Print length ‏ : ‎ 306 pages

OpenCL Programming by Example

Are you interested in learning how to harness the power of parallel computing using OpenCL? Look no further! In this post, we will walk you through some example programs to help you get started with OpenCL programming.

OpenCL, or Open Computing Language, is a framework for writing programs that execute across heterogeneous platforms consisting of CPUs, GPUs, and other processors. By using OpenCL, developers can take advantage of the parallel processing capabilities of these devices to accelerate their applications.

To begin with, let’s start by setting up a simple OpenCL program to add two arrays together. Here is a basic example of an OpenCL kernel that performs this task:

__kernel void add_arrays(__global const float *input1, __global const float *input2, __global float *output, const int size) {<br />
    int i = get_global_id(0);<br />
    <br />
    if (i < size) {<br />
        output[i] = input1[i] + input2[i];<br />
    }<br />
}<br />
```<br />
<br />
In this kernel, we define a function called `add_arrays` that takes two input arrays `input1` and `input2`, an output array `output`, and the size of the arrays as arguments. The `get_global_id(0)` function retrieves the global ID of the current work item, which is used to index into the arrays.<br />
<br />
Next, let's write the host code that will call this kernel and execute it on a device. Here is an example of how you can set up the host code in C++:<br />
<br />
```c++<br />
#include <CL/cl.hpp><br />
#include <iostream><br />
<br />
int main() {<br />
    // Initialize OpenCL<br />
    cl::Context context(CL_DEVICE_TYPE_GPU);<br />
    cl::Program program(context, "add.cl");<br />
    <br />
    // Create input and output arrays<br />
    std::vector<float> input1 = {1, 2, 3, 4, 5};<br />
    std::vector<float> input2 = {5, 4, 3, 2, 1};<br />
    std::vector<float> output(5);<br />
    <br />
    // Create buffers for input and output arrays<br />
    cl::Buffer inputBuffer1(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, sizeof(float) * input1.size(), input1.data());<br />
    cl::Buffer inputBuffer2(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, sizeof(float) * input2.size(), input2.data());<br />
    cl::Buffer outputBuffer(context, CL_MEM_WRITE_ONLY, sizeof(float) * output.size());<br />
    <br />
    // Create kernel and set arguments<br />
    cl::Kernel kernel(program, "add_arrays");<br />
    kernel.setArg(0, inputBuffer1);<br />
    kernel.setArg(1, inputBuffer2);<br />
    kernel.setArg(2, outputBuffer);<br />
    kernel.setArg(3, static_cast<int>(input1.size()));<br />
    <br />
    // Create command queue and enqueue kernel<br />
    cl::CommandQueue queue(context);<br />
    queue.enqueueNDRangeKernel(kernel, cl::NullRange, cl::NDRange(input1.size()));<br />
    <br />
    // Read output buffer<br />
    queue.enqueueReadBuffer(outputBuffer, CL_TRUE, 0, sizeof(float) * output.size(), output.data());<br />
    <br />
    // Print output<br />
    for (const auto& val : output) {<br />
        std::cout << val << " ";<br />
    }<br />
    <br />
    return 0;<br />
}<br />
```<br />
<br />
In this host code, we first initialize an OpenCL context and create a program from the kernel file "add.cl". We then create input and output arrays, as well as buffers for these arrays. We set the arguments for the kernel and enqueue it on a command queue for execution. Finally, we read the output buffer and print the results.<br />
<br />
This is just a simple example to get you started with OpenCL programming. As you become more comfortable with the framework, you can explore more advanced topics such as memory management, synchronization, and optimization techniques. Happy coding!

#OpenCL #Programming