sightolz.blogg.se - Apple metal gpu

I'm not going to go into how to calculate the thread groups in this post since it can get confusing fast, so copy the line of code shown below: NSUInteger width=kernelPSO.threadExecutionWidth Ok, finally, we need to dispatch our threads. Once we start writing the Kernel, you will see what I mean. And outBuf will be referenced using index 1. So, the inBuf will be referenced by using index 0. You do so by specifying indices using the command encoder: We must inform our Kernel how to reference the two buffers you created earlier. Note that the compute encoder is created using our newly created Command Buffer object. So, let's create an encoder and attach the pipeline. We need to link our Compute Pipeline previously created to an encoder. Id outBuf= įor (int i=0 i commandBuffer= Creating and loading buffers is shown below: id inBuf= We need to create two buffers and load them with data. We are almost done with our initialization routine. A command queue is created using the following line of code: id commandQueue= Load data into buffers The Command Queue will be responsible for sending our work to the GPU. Next, we need to get a reference to a Command Queue. Ok, so we have a device, a library, and a kernel reference. This Compute Pipeline will be attached to our encoder. We can now create a Compute Pipeline State with our kernel reference.

So, let's get a reference to our Kernel: id kernel=[defaultLibrary function declaration name of our Kernel is "inOutExample"

Now that we have a library object, we can create a reference to our Kernel.

A library is created as shown below: id defaultLibrary= This object will be responsible for compiling our Kernel. Once we have a device, we can create an MTLLibrary object. In Metal, this is done as follows: id device=MTLCreateSystemDefaultDevice() The first thing we need to do is to get a handle on our GPU device. #import Initialize device, library, and Command Queue In the main.m file, make sure to import these two libraries: #import The sample project is simple enough that you should be able to follow along). Next, select "Command Line Tool." Give a name to your project and choose "Objective-C" as the language.

Initialize our Device, Library and Command Queue.

Setup Xcode project for Compute kernels.

All our code will do is write data from one buffer onto another. Our example will be straightforward but will lay the foundation needed. Hey guys, I want to share how you can write your first GPU Kernel using Metal.