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TLDR - Quick Start

Create a new ILGPU Context instance that initializes ILGPU. Create Accelerator instances that target specific hardware devices. Compile and load the desired kernels and launch them with allocated chunks of memory. Retrieve the data and you're done 😄

Refer to the related ILGPU sample for additional insights.

class ...
{
    static void MyKernel(
        Index1 index, // The global thread index (1D in this case)
        ArrayView<int> dataView, // A view to a chunk of memory (1D in this case)
        int constant) // A sample uniform constant
    {
        dataView[index] = index + constant;
    }

    public static void Main(string[] args)
    {
        // Create the required ILGPU context
        using var context = new Context();
        using var accelerator = new CudaAccelerator(context);

        // accelerator.LoadAutoGroupedStreamKernel creates a typed launcher
        // that implicitly uses the default accelerator stream.
        // In order to create a launcher that receives a custom accelerator stream
        // use: accelerator.LoadAutoGroupedKernel<Index1, ArrayView<int> int>(...)
        var myKernel = accelerator.LoadAutoGroupedStreamKernel<
            Index1,
            ArrayView<int>,
            int>(MyKernel);

        // Allocate some memory
        using var buffer = accelerator.Allocate<int>(1024);
        // Launch buffer.Length many threads and pass a view to buffer
        myKernel(buffer.Length, buffer.View, 42);

        // Wait for the kernel to finish...
        accelerator.Synchronize();

        // Resolve data
        var data = buffer.GetAsArray();
        // ...
    }
}