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use crate::permutations::PermutationGenerator;
use crate::solvers::gpu::*;
use crate::solvers::{wall_stats, IteratorSolver, Solver};
use rayon::prelude::*;
use std::sync::mpsc::Sender;
use std::sync::{Arc, Mutex};
#[derive(Debug)]
pub struct GpuSolver {
n: u32,
h: u32,
w: u32,
chunk: u32,
permutations: Vec<Vec<u32>>,
masks: Vec<u64>,
progress: Arc<Mutex<u32>>,
}
impl GpuSolver {
fn solve_to_vec(&mut self) -> Vec<RowResult> {
let (sender, receiver) = std::sync::mpsc::channel();
if let Ok((sender, handle)) =
OclManager::launch_sevice(&self.permutations, &self.masks, self.n, 0, sender)
{
let chunk = permutohedron::factorial(self.n as usize - 1) as u32;
self.permute(
0,
0,
((0..(self.h - 2)).map(|x| x * chunk).collect::<Vec<u32>>()).as_ref(),
sender.clone(),
);
sender.send(Message::CpuDone).unwrap();
let mut walls = Vec::new();
while let Ok(Message::RowResult(wall)) = receiver.recv() {
walls.push(wall);
}
sender.send(Message::Terminate).unwrap();
//println!("{:?}", walls);
handle.join().unwrap();
return walls;
}
vec![]
}
fn permute(&self, index: usize, curr_mask: u64, numbers: &[u32], sender: Sender<Message>) {
if curr_mask.count_ones() < index as u32 * (self.n - 1) {
return;
}
let mut new_num = Vec::from(numbers);
if index as usize == numbers.len() {
let mut info = sys_info::mem_info().unwrap();
while info.avail < 1024 * 1024 {
std::thread::sleep(std::time::Duration::from_millis(500));
info = sys_info::mem_info().unwrap();
println!("mem wait {:?}", info);
}
let i = self.n - 3 - numbers[index - 1] / self.chunk;
let _ = sender
.send(Message::CheckRequest(CheckRequest::new(
new_num, curr_mask, i,
)))
.is_ok();
return;
}
let start = numbers[index as usize] / self.chunk;
for i in start..self.n - (self.h - 1 - index as u32) {
for n in 1..(numbers.len() - index) {
new_num[n + index] = (n as u32 + i) * self.chunk;
}
if index == 0 {
let senders: Vec<_> = (0..self.chunk).map(|_| sender.clone()).collect();
(0..self.chunk)
.into_par_iter()
.zip(senders)
.for_each(|(j, sender)| {
let mut new_num = new_num.clone();
let tmp = i * self.chunk + j;
new_num[index] = tmp;
self.permute(
index + 1,
curr_mask | self.masks[tmp as usize],
&new_num,
sender,
);
});
} else {
for j in 0..self.chunk {
let n_i = i * self.chunk + j;
if curr_mask & (1 << (self.permutations[n_i as usize][0] + 1)) > 0 {
continue;
}
new_num[index] = n_i;
self.permute(
index + 1,
curr_mask | self.masks[new_num[index] as usize],
&new_num,
sender.clone(),
);
}
if index == 1 {
let mut data = self.progress.lock().unwrap();
*data += 1;
let bias = self.n - (self.h - 1);
println!(
"progress: {}%",
*data as f64 / self.chunk as f64 * 50.0 / bias as f64
);
}
}
}
}
}
fn generate_permutations(n: u32) -> Vec<Vec<u32>> {
crate::permutations::HeapsPermutations::permutations(n)
}
fn generate_masks(permutations: &[Vec<u32>]) -> Vec<u64> {
let mut masks = Vec::with_capacity(permutations.len());
for p in permutations {
let mut v = 0;
let mut x = 0u64;
for i in p.iter().take(p.len() - 1).map(|i| {
v += i;
v
}) {
x |= 1 << i
}
masks.push(x)
}
masks
}
impl Solver for GpuSolver {
fn new(n: u32) -> Self {
let (h, w) = wall_stats(n);
let permutations = generate_permutations(n);
let masks = generate_masks(&permutations);
let chunk = permutohedron::factorial(n as usize - 1) as u32;
Self {
n,
h,
w,
chunk,
permutations,
masks,
progress: Arc::new(Mutex::new(0)),
}
}
fn n(&self) -> u32 {
self.n
}
fn h(&self) -> u32 {
self.h
}
fn w(&self) -> u32 {
self.w
}
}
impl IteratorSolver for GpuSolver {
type IntoIter = std::vec::IntoIter<RowResult>;
fn solve(mut self) -> Self::IntoIter {
self.solve_to_vec().into_iter()
}
}
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