Merge pull request #1184 from MatejKozlovsky/gpu-frame-inflight-cap

This commit is contained in:
Brandon Thomas 2026-10-13 04:29:08 -04:00
commit 7197d2fb7e
1 changed files with 236 additions and 2 deletions

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@ -15,6 +15,61 @@ use web_time::Instant;
use crate::{Job, RenderQuality, out};
/// GPU frames rendered at once by default: one, as the export scheduler's single GPU worker
/// renders image sequences (#898: frames in flight beyond one only with asynchronous YUV
/// readback). Measured on the #879 project at 1080p on an 8 GB card: 6.3 GB peak with one,
/// 7.0 to 7.8 GB with two, and the whole card with three, where main fell back to the CPU.
/// Not sized from free VRAM: the GPU backend reports no free or total device memory on every
/// platform, so a portable estimate is not available here.
pub(crate) const GPU_INFLIGHT_DEFAULT: usize = 1;
/// Overrides [`GPU_INFLIGHT_DEFAULT`]: a whole number of frames, at least 1.
pub(crate) const GPU_INFLIGHT_ENV: &str = "EFFECTCRAFT_GPU_INFLIGHT";
/// GPU frames in flight from the `EFFECTCRAFT_GPU_INFLIGHT` value: a positive whole number, or
/// the default (with a warning when a value was given) when it is 0, negative, not a number or
/// too large.
pub(crate) fn gpu_inflight(var: Option<&str>) -> usize {
let Some(v) = var else { return GPU_INFLIGHT_DEFAULT };
match v.trim().parse::<usize>() {
Ok(n) if n >= 1 => n,
_ => {
log::warn!(target: "effectcraft_export", "{GPU_INFLIGHT_ENV}={v:?} is not a whole number of frames of at least 1: using {GPU_INFLIGHT_DEFAULT}");
GPU_INFLIGHT_DEFAULT
}
}
}
/// `render` then `encode` over the frames `ks`, results in `ks` order.
///
/// Without `cap` every frame renders and encodes in one parallel batch (the CPU path, as
/// before). With `cap` (GPU frames in flight), the frames go in windows of
/// `max(cap, threads)`: each window renders in consecutive chunks of `cap` (at most `cap`
/// renders at once), then encodes in parallel, so only the render is serialised and at most
/// one window of rendered images is held in memory. Chunks hold no lock or slot, so a failing
/// or panicking frame cannot leak one, and nested parallelism (or a single thread) cannot
/// deadlock.
pub(crate) fn map_frames<I: Send, T: Send>(
ks: Vec<u64>,
cap: Option<usize>,
render: impl Fn(u64) -> I + Sync + Send,
encode: impl Fn(u64, I) -> T + Sync + Send,
) -> Vec<T> {
use rayon::prelude::*;
let Some(n) = cap.map(|n| n.max(1)) else {
return ks.into_par_iter().map(|k| encode(k, render(k))).collect();
};
let window = n.max(rayon::current_num_threads());
let mut out = Vec::with_capacity(ks.len());
for win in ks.chunks(window) {
let mut imgs = Vec::with_capacity(win.len());
for chunk in win.chunks(n) {
imgs.par_extend(chunk.par_iter().map(|&k| render(k)));
}
out.par_extend(win.par_iter().copied().zip(imgs.into_par_iter()).map(|(k, img)| encode(k, img)));
}
out
}
/// A job being exported: the job, the project with the Render Settings overrides applied, the
/// job's layer cache and per-frame timing for the render log.
pub(crate) struct Cx<'a> {
@ -132,8 +187,15 @@ impl<'a> Cx<'a> {
}
return out;
}
use rayon::prelude::*;
ks.into_par_iter().map(|k| f(k, self.frame(comp, k))).collect()
map_frames(ks, self.gpu_cap(), |k| self.frame(comp, k), f)
}
/// GPU frames rendered at once (#879), decided once per batch: with a GPU accelerator every
/// frame in flight holds its own working textures, so a whole batch rendered at once can
/// exhaust VRAM (or shared memory, which crashes instead of falling back). `None` when the
/// frames render on the CPU: no accelerator, or a Software Only project.
fn gpu_cap(&self) -> Option<usize> {
(self.job.accel.is_some() && self.project.settings.gpu_acceleration).then(|| gpu_inflight(std::env::var(GPU_INFLIGHT_ENV).ok().as_deref()))
}
/// Output frame `i`: sampled (fields, pulldown), at the colour depth, cropped and resized.
@ -367,6 +429,178 @@ fn premultiplied8(img: &Image) -> Vec<u8> {
#[cfg(test)]
mod tests {
use super::*;
use rayon::prelude::*;
/// Frames `0..n` through [`map_frames`] with `cap`, recording the most running at once.
fn run_capped(n: u64, cap: Option<usize>) -> (Vec<u64>, usize) {
use std::sync::atomic::{AtomicUsize, Ordering};
let (now, max) = (AtomicUsize::new(0), AtomicUsize::new(0));
let out = map_frames(
(0..n).collect(),
cap,
|k| {
let c = now.fetch_add(1, Ordering::SeqCst) + 1;
max.fetch_max(c, Ordering::SeqCst);
std::thread::sleep(std::time::Duration::from_millis(2));
now.fetch_sub(1, Ordering::SeqCst);
k
},
|k, img| {
assert_eq!(k, img);
k * 10
},
);
(out, max.load(Ordering::SeqCst))
}
#[test]
fn capped_frames_keep_their_order() {
let want: Vec<u64> = (0..40).map(|k| k * 10).collect();
for cap in [None, Some(1), Some(3), Some(7)] {
assert_eq!(run_capped(40, cap).0, want, "cap {cap:?}");
}
}
#[test]
fn gpu_frames_in_flight_respect_the_cap() {
// #879: every frame of a batch rendered on the GPU at once and exhausted VRAM.
let pool = rayon::ThreadPoolBuilder::new().num_threads(8).build().unwrap();
pool.install(|| {
for cap in [1, 2, 3] {
let (out, max) = run_capped(30, Some(cap));
assert_eq!(out.len(), 30);
assert!(max <= cap, "cap {cap}: {max} frames ran at once");
}
});
}
#[test]
fn a_cap_above_the_frame_count_renders_them_all() {
let (out, max) = run_capped(2, Some(8));
assert_eq!(out, vec![0, 10]);
assert!(max <= 2);
assert!(run_capped(0, Some(3)).0.is_empty());
}
#[test]
fn cap_one_on_a_single_thread_does_not_deadlock() {
let pool = rayon::ThreadPoolBuilder::new().num_threads(1).build().unwrap();
let (out, max) = pool.install(|| run_capped(10, Some(1)));
assert_eq!(out.len(), 10);
assert_eq!(max, 1);
// Nested parallelism inside a frame (as the renderer has) on one thread.
let out = pool.install(|| map_frames((0..6).collect(), Some(2), |k| (0..4u64).into_par_iter().map(|i| i + k).sum::<u64>(), |_, v| v));
assert_eq!(out, (0..6).map(|k| 6 + 4 * k).collect::<Vec<_>>());
}
#[test]
fn a_failing_frame_does_not_hold_up_the_rest() {
let out = map_frames((0..9).collect(), Some(1), |k| if k == 3 { Err(k) } else { Ok(k) }, |_, r| r);
assert_eq!(out.iter().filter(|r| r.is_err()).count(), 1);
assert_eq!(out.len(), 9);
assert_eq!(out[8], Ok(8));
// A panicking frame propagates once and leaves no slot behind: the next batch runs.
let r = std::panic::catch_unwind(|| map_frames((0..6).collect(), Some(2), |k| if k == 2 { panic!("frame {k}") } else { k }, |_, k| k));
assert!(r.is_err());
assert_eq!(run_capped(6, Some(2)).0.len(), 6);
}
#[test]
fn encoding_is_not_capped_with_the_render() {
// Only the GPU render is serialised: a window of frames encodes in parallel.
use std::sync::atomic::{AtomicUsize, Ordering};
let pool = rayon::ThreadPoolBuilder::new().num_threads(4).build().unwrap();
let (now, max) = (AtomicUsize::new(0), AtomicUsize::new(0));
let out = pool.install(|| {
map_frames(
(0..8).collect(),
Some(1),
|k| k,
|k, _| {
let c = now.fetch_add(1, Ordering::SeqCst) + 1;
max.fetch_max(c, Ordering::SeqCst);
std::thread::sleep(std::time::Duration::from_millis(20));
now.fetch_sub(1, Ordering::SeqCst);
k
},
)
});
assert_eq!(out, (0..8).collect::<Vec<_>>());
assert!(max.load(Ordering::SeqCst) > 1, "encodes ran one at a time");
}
/// An accelerator that renders nothing itself (the tests only check whether frames are capped).
struct NoAccel;
impl effectcraft_render::Accelerator for NoAccel {
fn name(&self) -> String {
"none".into()
}
fn comp_frame(&self, _r: &Renderer, _comp: effectcraft_project::ItemId, _t: Tick) -> Option<Image> {
None
}
fn supports_effect(&self, _id: &str) -> bool {
false
}
fn effects(&self, _chain: &[effectcraft_render::FxStep], _buf: &effectcraft_effects::Buf, _levels: Option<f32>) -> Option<effectcraft_effects::Buf> {
None
}
}
#[test]
fn software_only_projects_are_not_capped() {
// Review of #879: an accelerator alone capped Software Only projects, which render on the CPU.
use effectcraft_project::render_queue::{OutputFormat, OutputModule, RenderSettings};
use effectcraft_render::NoFootage;
let (settings, output) = (RenderSettings::default(), OutputModule::for_format(OutputFormat::PngSequence));
let accel = NoAccel;
for (gpu, want) in [(false, None), (true, Some(GPU_INFLIGHT_DEFAULT))] {
let mut p = Project::default();
p.settings.gpu_acceleration = gpu;
let job = Job {
project: &p,
footage: &NoFootage,
expr: None,
accel: Some(&accel),
comp: effectcraft_project::ItemId(0),
settings: &settings,
output: &output,
path: "/c/f_[#####].png",
sink: None,
nested_switches: true,
options: Default::default(),
};
if std::env::var_os(GPU_INFLIGHT_ENV).is_none() {
assert_eq!(Cx::new(&job).gpu_cap(), want, "gpu acceleration {gpu}");
} else {
assert_eq!(Cx::new(&job).gpu_cap().is_some(), gpu);
}
}
let p = Project::default();
let job = Job {
project: &p,
footage: &NoFootage,
expr: None,
accel: None,
comp: effectcraft_project::ItemId(0),
settings: &settings,
output: &output,
path: "/c/f_[#####].png",
sink: None,
nested_switches: true,
options: Default::default(),
};
assert_eq!(Cx::new(&job).gpu_cap(), None, "no accelerator");
}
#[test]
fn gpu_inflight_override_is_a_positive_number_or_the_default() {
assert_eq!(gpu_inflight(None), GPU_INFLIGHT_DEFAULT);
assert_eq!(gpu_inflight(Some("3")), 3);
assert_eq!(gpu_inflight(Some(" 5 ")), 5);
for bad in ["0", "", "-2", "three", "2.5", "99999999999999999999999"] {
assert_eq!(gpu_inflight(Some(bad)), GPU_INFLIGHT_DEFAULT, "{bad:?}");
}
}
#[test]
fn layers_render_once_per_job() {