Files
candle/candle-metal-kernels/tmp/unary.rs
2023-11-11 17:43:35 +01:00

198 lines
6.3 KiB
Rust

use candle_metal_kernels::{call_unary_contiguous, call_unary_strided, unary, Kernels};
use half::{bf16, f16};
use metal::objc::rc::autoreleasepool;
use metal::{Device, MTLResourceOptions};
use rand;
use std::any::type_name;
use std::time::Instant;
fn main() {
let device = Device::system_default().unwrap();
let kernels = Kernels::new();
let f32_1k = (0..1000).map(|_| rand::random::<f32>()).collect::<Vec<_>>();
let f32_10k = (0..10000)
.map(|_| rand::random::<f32>())
.collect::<Vec<_>>();
let f32_100k = (0..100000)
.map(|_| rand::random::<f32>())
.collect::<Vec<_>>();
let f16_map = |v: &[f32]| v.iter().map(|v| f16::from_f32(*v)).collect::<Vec<_>>();
let f16_1k = f16_map(&f32_1k);
let f16_10k = f16_map(&f32_10k);
let f16_100k = f16_map(&f32_100k);
let bf16_map = |v: &[f32]| v.iter().map(|v| bf16::from_f32(*v)).collect::<Vec<_>>();
let bf16_1k = bf16_map(&f32_1k);
let bf16_10k = bf16_map(&f32_10k);
let bf16_100k = bf16_map(&f32_100k);
let f32_ckernels = [
unary::contiguous::sin::FLOAT,
unary::contiguous::cos::FLOAT,
unary::contiguous::exp::FLOAT,
unary::contiguous::sqr::FLOAT,
unary::contiguous::sqrt::FLOAT,
unary::contiguous::neg::FLOAT,
unary::contiguous::copy::FLOAT,
];
let f32_skernels = [
unary::strided::sin::FLOAT,
unary::strided::cos::FLOAT,
unary::strided::exp::FLOAT,
unary::strided::sqr::FLOAT,
unary::strided::sqrt::FLOAT,
unary::strided::neg::FLOAT,
unary::strided::copy::FLOAT,
];
let f16_ckernels = [
unary::contiguous::sin::HALF,
unary::contiguous::cos::HALF,
unary::contiguous::exp::HALF,
unary::contiguous::sqr::HALF,
unary::contiguous::sqrt::HALF,
unary::contiguous::neg::HALF,
unary::contiguous::copy::HALF,
];
let f16_skernels = [
unary::strided::sin::HALF,
unary::strided::cos::HALF,
unary::strided::exp::HALF,
unary::strided::sqr::HALF,
unary::strided::sqrt::HALF,
unary::strided::neg::HALF,
unary::strided::copy::HALF,
];
let bf16_ckernels = [
unary::contiguous::sin::BFLOAT,
unary::contiguous::cos::BFLOAT,
unary::contiguous::exp::BFLOAT,
unary::contiguous::sqr::BFLOAT,
unary::contiguous::sqrt::BFLOAT,
unary::contiguous::neg::BFLOAT,
unary::contiguous::copy::BFLOAT,
];
let bf16_skernels = [
unary::strided::sin::BFLOAT,
unary::strided::cos::BFLOAT,
unary::strided::exp::BFLOAT,
unary::strided::sqr::BFLOAT,
unary::strided::sqrt::BFLOAT,
unary::strided::neg::BFLOAT,
unary::strided::copy::BFLOAT,
];
println!(
"{0: <5} | {1: <19} | {2: <6} | {3: <5} | {4: <11} | {5: <11}",
"dtype", "kernel", "size", "runs", "total time", "avg time"
);
// f32
run_unary_bench(&device, &kernels, &f32_1k, f32_ckernels, f32_skernels);
run_unary_bench(&device, &kernels, &f32_10k, f32_ckernels, f32_skernels);
run_unary_bench(&device, &kernels, &f32_100k, f32_ckernels, f32_skernels);
// f16
run_unary_bench(&device, &kernels, &f16_1k, f16_ckernels, f16_skernels);
run_unary_bench(&device, &kernels, &f16_10k, f16_ckernels, f16_skernels);
run_unary_bench(&device, &kernels, &f16_100k, f16_ckernels, f16_skernels);
// bf16
run_unary_bench(&device, &kernels, &bf16_1k, bf16_ckernels, bf16_skernels);
run_unary_bench(&device, &kernels, &bf16_10k, bf16_ckernels, bf16_skernels);
run_unary_bench(&device, &kernels, &bf16_100k, bf16_ckernels, bf16_skernels);
}
fn run_unary_bench<T: Clone>(
device: &Device,
kernels: &Kernels,
v: &[T],
contiguous: [unary::contiguous::Kernel; 7],
strided: [unary::strided::Kernel; 7],
) {
let command_queue = device.new_command_queue();
let options = MTLResourceOptions::StorageModeManaged;
let iterations = 10000;
let input = device.new_buffer_with_data(
v.as_ptr() as *const core::ffi::c_void,
core::mem::size_of_val(v) as u64,
options,
);
let mut output = device.new_buffer(core::mem::size_of_val(v) as u64, options);
// Contiguous
for kernel_name in contiguous {
let total_time = autoreleasepool(|| {
let command_buffer = command_queue.new_command_buffer();
let start = Instant::now();
for _ in 0..iterations {
call_unary_contiguous(
device,
&command_buffer,
kernels,
kernel_name,
v.len(),
&input,
&mut output,
)
.unwrap();
}
command_buffer.commit();
command_buffer.wait_until_completed();
start.elapsed()
});
println!(
"{0: <5} | {1: <19} | {2: <6} | {3: <5} | {4: <11?} | {5: <11?}",
type_name::<T>().split("::").last().unwrap(),
kernel_name.0,
v.len(),
iterations,
total_time,
total_time / iterations
);
}
// Strided
let shape = vec![2, 5_000];
let strides = vec![2, 1];
let offset = 0;
for kernel_name in &strided {
let total_time = autoreleasepool(|| {
let command_buffer = command_queue.new_command_buffer();
let start = Instant::now();
for _ in 0..iterations {
call_unary_strided(
device,
command_buffer,
&kernels,
kernel_name,
&shape,
&input,
&strides,
offset,
&mut output,
0,
)
.unwrap();
}
command_buffer.commit();
command_buffer.wait_until_completed();
start.elapsed()
});
println!(
"{0: <5} | {1: <19} | {2: <6} | {3: <5} | {4: <11?} | {5: <11?}",
type_name::<T>().split("::").last().unwrap(),
kernel_name.0,
v.len(),
iterations,
total_time,
total_time / iterations
);
}
}