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# shader-f16 | ||
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Demonstrate the ability to perform compute in F16 using wgpu. | ||
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## To Run | ||
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``` | ||
RUST_LOG=hello_compute cargo run --bin wgpu-examples shader_f16 | ||
``` |
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use half::f16; | ||
use std::{borrow::Cow, str::FromStr}; | ||
use wgpu::util::DeviceExt; | ||
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#[cfg_attr(test, allow(dead_code))] | ||
async fn run() { | ||
let numbers = if std::env::args().len() <= 2 { | ||
let default = vec![ | ||
f16::from_f32(27.), | ||
f16::from_f32(7.), | ||
f16::from_f32(5.), | ||
f16::from_f32(3.), | ||
]; | ||
println!("No numbers were provided, defaulting to {default:?}"); | ||
default | ||
} else { | ||
std::env::args() | ||
.skip(2) | ||
.map(|s| f16::from_str(&s).expect("You must pass a list of positive integers!")) | ||
.collect() | ||
}; | ||
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let steps = execute_gpu(&numbers).await.unwrap(); | ||
println!("Steps: [{:?}]", steps); | ||
#[cfg(target_arch = "wasm32")] | ||
log::info!("Steps: [{:?}]", steps); | ||
} | ||
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#[cfg_attr(test, allow(dead_code))] | ||
async fn execute_gpu(numbers: &[f16]) -> Option<Vec<f16>> { | ||
// Instantiates instance of WebGPU | ||
let instance = wgpu::Instance::default(); | ||
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// `request_adapter` instantiates the general connection to the GPU | ||
let adapter = instance | ||
.request_adapter(&wgpu::RequestAdapterOptions::default()) | ||
.await?; | ||
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// `request_device` instantiates the feature specific connection to the GPU, defining some parameters, | ||
// `features` being the available features. | ||
let (device, queue) = adapter | ||
.request_device( | ||
&wgpu::DeviceDescriptor { | ||
label: None, | ||
required_features: wgpu::Features::SHADER_F16, | ||
required_limits: wgpu::Limits::downlevel_defaults(), | ||
memory_hints: Default::default(), | ||
}, | ||
None, | ||
) | ||
.await | ||
.unwrap(); | ||
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execute_gpu_inner(&device, &queue, numbers).await | ||
} | ||
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async fn execute_gpu_inner( | ||
device: &wgpu::Device, | ||
queue: &wgpu::Queue, | ||
numbers: &[f16], | ||
) -> Option<Vec<f16>> { | ||
// Loads the shader from WGSL | ||
let cs_module = device.create_shader_module(wgpu::ShaderModuleDescriptor { | ||
label: None, | ||
source: wgpu::ShaderSource::Wgsl(Cow::Borrowed(include_str!("shader.wgsl"))), | ||
}); | ||
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// Gets the size in bytes of the buffer. | ||
let size = std::mem::size_of_val(numbers) as wgpu::BufferAddress; | ||
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// Instantiates buffer without data. | ||
// `usage` of buffer specifies how it can be used: | ||
// `BufferUsages::MAP_READ` allows it to be read (outside the shader). | ||
// `BufferUsages::COPY_DST` allows it to be the destination of the copy. | ||
let staging_buffer = device.create_buffer(&wgpu::BufferDescriptor { | ||
label: None, | ||
size, | ||
usage: wgpu::BufferUsages::MAP_READ | wgpu::BufferUsages::COPY_DST, | ||
mapped_at_creation: false, | ||
}); | ||
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// Instantiates buffer with data (`numbers`). | ||
// Usage allowing the buffer to be: | ||
// A storage buffer (can be bound within a bind group and thus available to a shader). | ||
// The destination of a copy. | ||
// The source of a copy. | ||
let storage_buffer = device.create_buffer_init(&wgpu::util::BufferInitDescriptor { | ||
label: Some("Storage Buffer"), | ||
contents: bytemuck::cast_slice(numbers), | ||
usage: wgpu::BufferUsages::STORAGE | ||
| wgpu::BufferUsages::COPY_DST | ||
| wgpu::BufferUsages::COPY_SRC, | ||
}); | ||
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// A bind group defines how buffers are accessed by shaders. | ||
// It is to WebGPU what a descriptor set is to Vulkan. | ||
// `binding` here refers to the `binding` of a buffer in the shader (`layout(set = 0, binding = 0) buffer`). | ||
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// A pipeline specifies the operation of a shader | ||
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// Instantiates the pipeline. | ||
let compute_pipeline = device.create_compute_pipeline(&wgpu::ComputePipelineDescriptor { | ||
label: None, | ||
layout: None, | ||
module: &cs_module, | ||
entry_point: None, | ||
compilation_options: Default::default(), | ||
cache: None, | ||
}); | ||
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// Instantiates the bind group, once again specifying the binding of buffers. | ||
let bind_group_layout = compute_pipeline.get_bind_group_layout(0); | ||
let bind_group = device.create_bind_group(&wgpu::BindGroupDescriptor { | ||
label: None, | ||
layout: &bind_group_layout, | ||
entries: &[wgpu::BindGroupEntry { | ||
binding: 0, | ||
resource: storage_buffer.as_entire_binding(), | ||
}], | ||
}); | ||
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// A command encoder executes one or many pipelines. | ||
// It is to WebGPU what a command buffer is to Vulkan. | ||
let mut encoder = | ||
device.create_command_encoder(&wgpu::CommandEncoderDescriptor { label: None }); | ||
{ | ||
let mut cpass = encoder.begin_compute_pass(&wgpu::ComputePassDescriptor { | ||
label: None, | ||
timestamp_writes: None, | ||
}); | ||
cpass.set_pipeline(&compute_pipeline); | ||
cpass.set_bind_group(0, Some(&bind_group), &[]); | ||
cpass.insert_debug_marker("compute collatz iterations"); | ||
cpass.dispatch_workgroups(numbers.len() as u32, 1, 1); // Number of cells to run, the (x,y,z) size of item being processed | ||
} | ||
// Sets adds copy operation to command encoder. | ||
// Will copy data from storage buffer on GPU to staging buffer on CPU. | ||
encoder.copy_buffer_to_buffer(&storage_buffer, 0, &staging_buffer, 0, size); | ||
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// Submits command encoder for processing | ||
queue.submit(Some(encoder.finish())); | ||
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// Note that we're not calling `.await` here. | ||
let buffer_slice = staging_buffer.slice(..); | ||
// Sets the buffer up for mapping, sending over the result of the mapping back to us when it is finished. | ||
let (sender, receiver) = flume::bounded(1); | ||
buffer_slice.map_async(wgpu::MapMode::Read, move |v| sender.send(v).unwrap()); | ||
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// Poll the device in a blocking manner so that our future resolves. | ||
// In an actual application, `device.poll(...)` should | ||
// be called in an event loop or on another thread. | ||
device.poll(wgpu::Maintain::wait()).panic_on_timeout(); | ||
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// Awaits until `buffer_future` can be read from | ||
if let Ok(Ok(())) = receiver.recv_async().await { | ||
// Gets contents of buffer | ||
let data = buffer_slice.get_mapped_range(); | ||
// Since contents are got in bytes, this converts these bytes back to u32 | ||
let result = bytemuck::cast_slice(&data).to_vec(); | ||
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// With the current interface, we have to make sure all mapped views are | ||
// dropped before we unmap the buffer. | ||
drop(data); | ||
staging_buffer.unmap(); // Unmaps buffer from memory | ||
// If you are familiar with C++ these 2 lines can be thought of similarly to: | ||
// delete myPointer; | ||
// myPointer = NULL; | ||
// It effectively frees the memory | ||
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// Returns data from buffer | ||
Some(result) | ||
} else { | ||
panic!("failed to run compute on gpu!") | ||
} | ||
} | ||
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pub fn main() { | ||
#[cfg(not(target_arch = "wasm32"))] | ||
{ | ||
env_logger::init(); | ||
pollster::block_on(run()); | ||
} | ||
#[cfg(target_arch = "wasm32")] | ||
{ | ||
std::panic::set_hook(Box::new(console_error_panic_hook::hook)); | ||
console_log::init().expect("could not initialize logger"); | ||
wasm_bindgen_futures::spawn_local(run()); | ||
} | ||
} |
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enable f16; | ||
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@group(0) @binding(0) | ||
var<storage, read_write> values: array<vec4<f16>>; // this is used as both values and output for convenience | ||
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@compute @workgroup_size(1) | ||
fn main(@builtin(global_invocation_id) global_id: vec3<u32>) { | ||
values[global_id.x] = fma(values[0], values[0], values[0]); | ||
} |
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