Struct Kernel

pub struct Kernel<'a> {
    pub builder: ExecuteKernel<'a>,
    /* private fields */
}

A kernel that can be executed.

Fields

builder: ExecuteKernel<'a>

The underlying kernel builder.

Implementations

impl<'a> Kernel<'a>

pub fn arg<T: KernelArgument>(self, t: &'a T) -> Self

Set a kernel argument.

The arguments must live as long as the kernel. Hence make sure they are not dropped as long as the kernel is in use.

Example where this behaviour is enforced and leads to a compile-time error:

use rust_gpu_tools::opencl::Program;

fn would_break(program: &Program) {
   let data = vec![1, 2, 3, 4];
   let buffer = program.create_buffer_from_slice(&data).unwrap();
   let kernel = program.create_kernel("my_kernel", 4, 256).unwrap();
   let kernel = kernel.arg(&buffer);
   // This drop wouldn't error if the arguments wouldn't be bound to the kernels lifetime.
   drop(buffer);
   kernel.run().unwrap();
}

Examples found in repository

examples/add.rs (line 45)

pub fn main() {
    // Define some data that should be operated on.
    let aa: Vec<u32> = vec![1, 2, 3, 4];
    let bb: Vec<u32> = vec![5, 6, 7, 8];

    // This is the core. Here we write the interaction with the GPU independent of whether it is
    // CUDA or OpenCL.
    let closures = program_closures!(|program, _args| -> Result<Vec<u32>, GPUError> {
        // Make sure the input data has the same length.
        assert_eq!(aa.len(), bb.len());
        let length = aa.len();

        // Copy the data to the GPU.
        let aa_buffer = program.create_buffer_from_slice(&aa)?;
        let bb_buffer = program.create_buffer_from_slice(&bb)?;

        // The result buffer has the same length as the input buffers.
        let result_buffer = unsafe { program.create_buffer::<u32>(length)? };

        // Get the kernel.
        let kernel = program.create_kernel("add", 1, 1)?;

        // Execute the kernel.
        kernel
            .arg(&(length as u32))
            .arg(&aa_buffer)
            .arg(&bb_buffer)
            .arg(&result_buffer)
            .run()?;

        // Get the resulting data.
        let mut result = vec![0u32; length];
        program.read_into_buffer(&result_buffer, &mut result)?;

        Ok(result)
    });

    // Get the first available device.
    let device = *Device::all().first().unwrap();

    // First we run it on CUDA.
    let cuda_program = cuda(device);
    let cuda_result = cuda_program.run(closures, ()).unwrap();
    assert_eq!(cuda_result, [6, 8, 10, 12]);
    println!("CUDA result: {:?}", cuda_result);

    // Then we run it on OpenCL.
    let opencl_program = opencl(device);
    let opencl_result = opencl_program.run(closures, ()).unwrap();
    assert_eq!(opencl_result, [6, 8, 10, 12]);
    println!("OpenCL result: {:?}", opencl_result);
}

pub fn run(self) -> Result<(), GPUError>

Actually run the kernel.

Examples found in repository

examples/add.rs (line 49)

pub fn main() {
    // Define some data that should be operated on.
    let aa: Vec<u32> = vec![1, 2, 3, 4];
    let bb: Vec<u32> = vec![5, 6, 7, 8];

    // This is the core. Here we write the interaction with the GPU independent of whether it is
    // CUDA or OpenCL.
    let closures = program_closures!(|program, _args| -> Result<Vec<u32>, GPUError> {
        // Make sure the input data has the same length.
        assert_eq!(aa.len(), bb.len());
        let length = aa.len();

        // Copy the data to the GPU.
        let aa_buffer = program.create_buffer_from_slice(&aa)?;
        let bb_buffer = program.create_buffer_from_slice(&bb)?;

        // The result buffer has the same length as the input buffers.
        let result_buffer = unsafe { program.create_buffer::<u32>(length)? };

        // Get the kernel.
        let kernel = program.create_kernel("add", 1, 1)?;

        // Execute the kernel.
        kernel
            .arg(&(length as u32))
            .arg(&aa_buffer)
            .arg(&bb_buffer)
            .arg(&result_buffer)
            .run()?;

        // Get the resulting data.
        let mut result = vec![0u32; length];
        program.read_into_buffer(&result_buffer, &mut result)?;

        Ok(result)
    });

    // Get the first available device.
    let device = *Device::all().first().unwrap();

    // First we run it on CUDA.
    let cuda_program = cuda(device);
    let cuda_result = cuda_program.run(closures, ()).unwrap();
    assert_eq!(cuda_result, [6, 8, 10, 12]);
    println!("CUDA result: {:?}", cuda_result);

    // Then we run it on OpenCL.
    let opencl_program = opencl(device);
    let opencl_result = opencl_program.run(closures, ()).unwrap();
    assert_eq!(opencl_result, [6, 8, 10, 12]);
    println!("OpenCL result: {:?}", opencl_result);
}

Trait Implementations

impl<'a> Debug for Kernel<'a>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.