mirror of
https://github.com/kenba/opencl3.git
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128 lines
4.7 KiB
Rust
128 lines
4.7 KiB
Rust
// Copyright (c) 2021 Via Technology Ltd. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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use opencl3::Result;
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use opencl3::command_queue::{CL_QUEUE_PROFILING_ENABLE, CommandQueue};
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use opencl3::context::Context;
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use opencl3::device::{CL_DEVICE_TYPE_GPU, Device, get_all_devices};
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use opencl3::kernel::{ExecuteKernel, Kernel};
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use opencl3::memory::{Buffer, CL_MEM_READ_ONLY, CL_MEM_WRITE_ONLY};
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use opencl3::program::Program;
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use opencl3::types::{CL_BLOCKING, CL_NON_BLOCKING, cl_event, cl_float};
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use std::ptr;
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const PROGRAM_SOURCE: &str = r#"
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kernel void saxpy_float (global float* z,
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global float const* x,
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global float const* y,
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float a)
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{
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const size_t i = get_global_id(0);
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z[i] = a*x[i] + y[i];
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}"#;
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const KERNEL_NAME: &str = "saxpy_float";
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fn main() -> Result<()> {
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// Find a usable device for this application
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let device_id = *get_all_devices(CL_DEVICE_TYPE_GPU)?
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.first()
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.expect("no device found in platform");
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let device = Device::new(device_id);
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// Create a Context on an OpenCL device
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let context = Context::from_device(&device).expect("Context::from_device failed");
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// Create a command_queue on the Context's device
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let queue = CommandQueue::create_default(&context, CL_QUEUE_PROFILING_ENABLE)
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.expect("CommandQueue::create_default failed");
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// Build the OpenCL program source and create the kernel.
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let program = Program::create_and_build_from_source(&context, PROGRAM_SOURCE, "")
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.expect("Program::create_and_build_from_source failed");
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let kernel = Kernel::create(&program, KERNEL_NAME).expect("Kernel::create failed");
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/////////////////////////////////////////////////////////////////////
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// Compute data
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// The input data
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const ARRAY_SIZE: usize = 1000;
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let ones: [cl_float; ARRAY_SIZE] = [1.0; ARRAY_SIZE];
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let mut sums: [cl_float; ARRAY_SIZE] = [0.0; ARRAY_SIZE];
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for i in 0..ARRAY_SIZE {
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sums[i] = 1.0 + 1.0 * i as cl_float;
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}
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// Create OpenCL device buffers
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let mut x = unsafe {
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Buffer::<cl_float>::create(&context, CL_MEM_READ_ONLY, ARRAY_SIZE, ptr::null_mut())?
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};
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let mut y = unsafe {
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Buffer::<cl_float>::create(&context, CL_MEM_READ_ONLY, ARRAY_SIZE, ptr::null_mut())?
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};
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let z = unsafe {
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Buffer::<cl_float>::create(&context, CL_MEM_WRITE_ONLY, ARRAY_SIZE, ptr::null_mut())?
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};
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// Blocking write
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let _x_write_event = unsafe { queue.enqueue_write_buffer(&mut x, CL_BLOCKING, 0, &ones, &[])? };
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// Non-blocking write, wait for y_write_event
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let y_write_event =
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unsafe { queue.enqueue_write_buffer(&mut y, CL_NON_BLOCKING, 0, &sums, &[])? };
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// a value for the kernel function
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let a: cl_float = 300.0;
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// Use the ExecuteKernel builder to set the kernel buffer and
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// cl_float value arguments, before setting the one dimensional
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// global_work_size for the call to enqueue_nd_range.
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// Unwraps the Result to get the kernel execution event.
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let kernel_event = unsafe {
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ExecuteKernel::new(&kernel)
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.set_arg(&z)
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.set_arg(&x)
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.set_arg(&y)
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.set_arg(&a)
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.set_global_work_size(ARRAY_SIZE)
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.set_wait_event(&y_write_event)
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.enqueue_nd_range(&queue)?
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};
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let mut events: Vec<cl_event> = Vec::default();
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events.push(kernel_event.get());
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// Create a results array to hold the results from the OpenCL device
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// and enqueue a read command to read the device buffer into the array
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// after the kernel event completes.
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let mut results: [cl_float; ARRAY_SIZE] = [0.0; ARRAY_SIZE];
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let read_event =
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unsafe { queue.enqueue_read_buffer(&z, CL_NON_BLOCKING, 0, &mut results, &events)? };
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// Wait for the read_event to complete.
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read_event.wait()?;
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// Output the first and last results
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println!("results front: {}", results[0]);
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println!("results back: {}", results[ARRAY_SIZE - 1]);
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// Calculate the kernel duration, from the kernel_event
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let start_time = kernel_event.profiling_command_start()?;
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let end_time = kernel_event.profiling_command_end()?;
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let duration = end_time - start_time;
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println!("kernel execution duration (ns): {}", duration);
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Ok(())
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}
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