refactor(numa): replace flat runner with per-node activation channels

Shifts the NUMA-aware runner from a flat, round-robin model to a per-node architecture using dedicated `NodeActivation` channels. Replaces absolute deltas with relative scaling based on the previous growth step's worker count, decoupling growth from node count to fix slow ramp-up and enforce per-node fairness. Updates architecture documentation to reflect these changes and focus tuning questions on `INITIAL`/`GROWTH_DIVISOR` parameters for I/O-bound validation.
This commit is contained in:
Eric Coissac
2026-07-03 12:47:56 +02:00
parent 66ab4c6db1
commit 67b4e4da53
2 changed files with 285 additions and 108 deletions
+217 -91
View File
@@ -70,7 +70,10 @@ pub fn build() -> NumaSetup {
nodes.len(),
nodes.first().map_or(0, |v| v.len()),
);
return NumaSetup { pools, cpus_per_node: nodes };
return NumaSetup {
pools,
cpus_per_node: nodes,
};
}
}
}
@@ -81,7 +84,7 @@ pub fn build() -> NumaSetup {
.unwrap_or(1);
debug!("UMA: single synthetic node, {} core(s)", n_cores);
NumaSetup {
pools: vec![None],
pools: vec![None],
cpus_per_node: vec![(0..n_cores).collect()],
}
}
@@ -93,7 +96,7 @@ pub fn build() -> NumaSetup {
.unwrap_or(1);
debug!("UMA: single synthetic node, {} core(s)", n_cores);
NumaSetup {
pools: vec![None],
pools: vec![None],
cpus_per_node: vec![(0..n_cores).collect()],
}
}
@@ -102,7 +105,9 @@ pub fn build() -> NumaSetup {
/// Silently returns on any error so the thread still runs, just unbound.
#[cfg(feature = "numa")]
pub fn pin_current_thread(cpu_indices: &[usize]) {
let Ok(topology) = Topology::new() else { return };
let Ok(topology) = Topology::new() else {
return;
};
let mut cpuset = CpuSet::new();
for &idx in cpu_indices {
cpuset.set(idx);
@@ -132,29 +137,48 @@ fn build_pool(cpus: &[usize]) -> Option<rayon::ThreadPool> {
.ok()
}
// ── PartitionRunner ───────────────────────────────────────────────────────────
// ── PartitionRunner ─────────────────────────────────────────────────────────
/// Growth step (fraction of a node's worker capacity added per activation
/// event, see [`NodeActivation::grow`]).
const GROWTH_DIVISOR: usize = 8;
/// Minimum CPU efficiency growth to activate more workers, as a fraction of
/// the size of the *last growth step* (e.g. `0.2` after adding 8 workers
/// requires the next check to show at least +1.6 cores of growth — 20 % of
/// the ~8 cores those 8 workers should contribute if the workload is truly
/// CPU-bound). Scaling by the last step's size — not the cumulative total —
/// keeps the bar meaningful regardless of how many workers are already
/// active, instead of demanding an ever-larger absolute jump as the pool
/// grows.
const CPU_SPAWN_THRESHOLD: f64 = 0.2;
/// Minimum I/O throughput growth (relative) to activate more workers.
const IO_SPAWN_THRESHOLD: f64 = 0.2;
struct NodeConfig {
pool: Option<Arc<rayon::ThreadPool>>,
cpu_ids: Vec<usize>,
pool: Option<Arc<rayon::ThreadPool>>,
cpu_ids: Vec<usize>,
max_workers: usize,
}
/// Generic NUMA-aware runner for partition-level parallel work.
///
/// Workers are distributed round-robin across NUMA nodes and pinned to their
/// Workers are distributed evenly across NUMA nodes and pinned to their
/// node's CPUs. UMA is the degenerate case: one node, no pinning.
///
/// Workers are pre-spawned dormant and activated one by one as CPU efficiency
/// falls below `SPAWN_THRESHOLD`. This avoids over-provisioning on I/O-bound
/// or memory-bandwidth-bound workloads while saturating CPU-bound ones.
/// Workers are pre-spawned dormant, one activation channel per node so
/// growth always targets a specific node rather than whichever dormant
/// worker happens to wake up first on a shared channel. Growth (both the
/// initial count and each subsequent step) is expressed as a fraction of
/// `workers_per_node`, applied identically to every node, so the pace of
/// ramp-up depends on node size rather than node count — a single-NUMA-node
/// (UMA) machine ramps just as fast as an 8-node one.
///
/// # Termination
///
/// ```text
/// drop(part_tx) → part_rx drains → workers exit → drop their result_tx
/// drop(result_tx) → result_rx closes → controller loop exits
/// drop(activate_tx) → dormant workers exit cleanly
/// drop(part_tx) → part_rx drains → workers exit → drop their result_tx
/// drop(result_tx) → result_rx closes → controller loop exits
/// drop(activate_txs) → dormant workers exit cleanly
/// ```
pub struct PartitionRunner {
nodes: Vec<NodeConfig>,
@@ -175,7 +199,8 @@ impl PartitionRunner {
ns.pools.len(),
wpn,
);
let nodes = ns.pools
let nodes = ns
.pools
.into_iter()
.zip(ns.cpus_per_node)
.map(|(pool, cpu_ids)| NodeConfig {
@@ -189,26 +214,24 @@ impl PartitionRunner {
/// Run `f(i)` for every index in `order`.
///
/// Workers are pre-spawned dormant and activated adaptively. A timer thread
/// fires an efficiency check every `TIMER_SECS` seconds; each completed
/// partition resets that timer (forcing an immediate check) and also
/// triggers its own inline check. A new worker is activated whenever CPU
/// efficiency grows by at least `CPU_SPAWN_THRESHOLD` (absolute, in cores)
/// or I/O throughput grows by at least `IO_SPAWN_THRESHOLD` (relative) since
/// the last check — whichever resource is the actual bottleneck still shows
/// headroom.
/// Workers are pre-spawned dormant and activated adaptively, per node:
/// `(workers_per_node / INITIAL_DIVISOR).max(1)` are woken immediately on
/// every node, then `(workers_per_node / GROWTH_DIVISOR).max(1)` more per
/// node each time the check below fires. A timer thread fires that check
/// every `TIMER_SECS` seconds; each completed partition resets that timer
/// (forcing an immediate check) and also triggers its own inline check. A
/// growth step happens whenever CPU efficiency grows by at least
/// `CPU_SPAWN_THRESHOLD` of what the last growth step should have
/// contributed, or I/O throughput grows by at least `IO_SPAWN_THRESHOLD`
/// (relative) since the last check — whichever resource is the actual
/// bottleneck still shows headroom.
///
/// `on_done(i, result, elapsed)` is called from the controller thread as
/// each partition completes — suitable for progress bars and result
/// aggregation.
///
/// Returns the first error produced by `f`, if any.
pub fn run<F, R, E, C>(
&self,
order: &[usize],
f: F,
mut on_done: C,
) -> Result<(), E>
pub fn run<F, R, E, C>(&self, order: &[usize], f: F, mut on_done: C) -> Result<(), E>
where
F: Fn(usize) -> Result<R, E> + Send + Sync,
R: Send,
@@ -220,24 +243,29 @@ impl PartitionRunner {
return Ok(());
}
const CPU_SPAWN_THRESHOLD: f64 = 0.2;
const IO_SPAWN_THRESHOLD: f64 = 0.2;
const TIMER_SECS: u64 = 30;
const TIMER_SECS: u64 = 30;
const INITIAL_DIVISOR: usize = 4;
// ── Channels ──────────────────────────────────────────────────────────
let (part_tx, part_rx) = unbounded::<usize>();
let (activate_tx, activate_rx) = unbounded::<()>();
let (part_tx, part_rx) = unbounded::<usize>();
// reset_tx: controller → timer ("reset the 30 s window")
let (reset_tx, reset_rx) = unbounded::<()>();
let (reset_tx, reset_rx) = unbounded::<()>();
// event_tx: workers + timer → controller (unified event stream)
let (event_tx, event_rx) = unbounded::<WorkerEvent<R, E>>();
let (event_tx, event_rx) = unbounded::<WorkerEvent<R, E>>();
// One activation channel per node: growth always targets a specific
// node, rather than whichever dormant worker happens to win the race
// on a channel shared across all nodes.
let (activate_txs, activate_rxs): (Vec<_>, Vec<_>) =
(0..self.nodes.len()).map(|_| unbounded::<()>()).unzip();
for &i in order { part_tx.send(i).ok(); }
for &i in order {
part_tx.send(i).ok();
}
drop(part_tx);
let max_workers = self.max_workers();
let n_nodes = self.nodes.len();
let f = &f;
let node_caps: Vec<usize> = self.nodes.iter().map(|n| n.max_workers).collect();
let f = &f;
let mut first_err: Option<E> = None;
@@ -260,79 +288,92 @@ impl PartitionRunner {
}
});
// ── Pre-spawn workers dormant, round-robin across NUMA nodes ──────
for w in 0..max_workers {
let node = &self.nodes[w % n_nodes];
let prx = part_rx.clone();
let etx = event_tx.clone();
let arx = activate_rx.clone();
let pool = node.pool.clone();
// ── Pre-spawn workers dormant, grouped by node ────────────────────
// Each worker listens on its own node's activation channel only.
for (node, arx) in self.nodes.iter().zip(activate_rxs.iter()) {
let cpu_ids = &node.cpu_ids;
for _ in 0..node.max_workers {
let prx = part_rx.clone();
let etx = event_tx.clone();
let arx = arx.clone();
let pool = node.pool.clone();
s.spawn(move || {
if arx.recv().is_err() { return; }
if !cpu_ids.is_empty() { pin_current_thread(cpu_ids); }
for i in &prx {
let t = Instant::now();
let r = match &pool {
Some(p) => p.install(|| f(i)),
None => f(i),
};
etx.send(WorkerEvent::Completed(i, r, t.elapsed())).ok();
}
});
s.spawn(move || {
if arx.recv().is_err() {
return;
}
if !cpu_ids.is_empty() {
pin_current_thread(cpu_ids);
}
for i in &prx {
let t = Instant::now();
let r = match &pool {
Some(p) => p.install(|| f(i)),
None => f(i),
};
etx.send(WorkerEvent::Completed(i, r, t.elapsed())).ok();
}
});
}
}
// Drop controller's event_tx: event_rx closes when all workers +
// timer have exited.
drop(event_tx);
// ── Controller ────────────────────────────────────────────────────
let initial_workers = n_nodes.min(max_workers).min(n_total);
for _ in 0..initial_workers { activate_tx.send(()).ok(); }
let mut n_active = initial_workers;
let mut activation = NodeActivation::new(&activate_txs, &node_caps, max_workers);
activation.activate_initial(INITIAL_DIVISOR, n_total);
let mut cpu_sample = CpuSample::now();
let mut io_sample = IoSample::now();
let mut completed = 0usize;
let mut io_sample = IoSample::now();
let mut completed = 0usize;
while completed < n_total {
let Ok(event) = event_rx.recv() else { break };
match event {
WorkerEvent::Completed(i, r, dur) => {
match r {
Ok(v) => on_done(i, v, dur),
Err(e) => { if first_err.is_none() { first_err = Some(e); } }
Ok(v) => on_done(i, v, dur),
Err(e) => {
if first_err.is_none() {
first_err = Some(e);
}
}
}
completed += 1;
// Reset the 30 s timer.
reset_tx.send(()).ok();
// Inline check: same logic as a timer tick.
maybe_activate(
&activate_tx, &mut n_active, max_workers,
&mut cpu_sample, CPU_SPAWN_THRESHOLD,
&mut io_sample, IO_SPAWN_THRESHOLD,
completed, n_total,
&mut activation,
&mut cpu_sample,
&mut io_sample,
completed,
n_total,
);
}
WorkerEvent::TimerTick => {
maybe_activate(
&activate_tx, &mut n_active, max_workers,
&mut cpu_sample, CPU_SPAWN_THRESHOLD,
&mut io_sample, IO_SPAWN_THRESHOLD,
completed, n_total,
&mut activation,
&mut cpu_sample,
&mut io_sample,
completed,
n_total,
);
}
}
}
// Dormant workers exit when activate_tx closes.
drop(activate_tx);
// Dormant workers exit once every sender for their node's channel
// is dropped — `activate_txs` holds the only ones.
drop(activate_txs);
// Timer thread exits when reset_tx closes.
drop(reset_tx);
});
match first_err {
Some(e) => Err(e),
None => Ok(()),
None => Ok(()),
}
}
}
@@ -344,28 +385,113 @@ enum WorkerEvent<R, E> {
TimerTick,
}
/// Tracks how many of each node's dormant workers have been woken, and
/// grows every node by the same amount at each step (capped by that node's
/// remaining dormant workers and by the run's total budget) so load stays
/// balanced across nodes at every point in time — never just "one more
/// worker somewhere". Also remembers the size of the last real growth step
/// (`last_step`), used to scale the CPU activation threshold to what that
/// step could plausibly have contributed (see `maybe_activate`).
struct NodeActivation<'a> {
txs: &'a [crossbeam_channel::Sender<()>],
caps: &'a [usize],
active: Vec<usize>,
total: usize,
max: usize,
last_step: usize,
}
impl<'a> NodeActivation<'a> {
fn new(txs: &'a [crossbeam_channel::Sender<()>], caps: &'a [usize], max: usize) -> Self {
Self {
txs,
caps,
active: vec![0; txs.len()],
total: 0,
max,
last_step: 0,
}
}
fn total(&self) -> usize {
self.total
}
fn last_step(&self) -> usize {
self.last_step
}
fn max(&self) -> usize {
self.max
}
fn is_full(&self) -> bool {
self.total >= self.max
}
/// Wake up to `(node_cap / divisor).max(1)` dormant workers on every
/// node, capped by `n_total`. Called once at startup, unconditionally.
fn activate_initial(&mut self, divisor: usize, n_total: usize) {
self.grow(divisor, n_total);
}
/// Same per-node sizing as [`activate_initial`](Self::activate_initial),
/// applied as a growth step. Returns the number of workers actually
/// activated (may be less than requested once a node or the total
/// budget is exhausted). Updates `last_step` when it actually grew.
fn grow(&mut self, divisor: usize, n_total: usize) -> usize {
let before = self.total;
for idx in 0..self.txs.len() {
let wanted = (self.caps[idx] / divisor).max(1);
let room = self.caps[idx].saturating_sub(self.active[idx]);
let grow = wanted.min(room).min(n_total.saturating_sub(self.total));
for _ in 0..grow {
self.txs[idx].send(()).ok();
}
self.active[idx] += grow;
self.total += grow;
}
let grew = self.total - before;
if grew > 0 {
self.last_step = grew;
}
grew
}
}
fn maybe_activate(
activate_tx: &crossbeam_channel::Sender<()>,
n_active: &mut usize,
max_workers: usize,
cpu_sample: &mut CpuSample,
cpu_threshold: f64,
io_sample: &mut IoSample,
io_threshold: f64,
completed: usize,
n_total: usize,
activation: &mut NodeActivation,
cpu_sample: &mut CpuSample,
io_sample: &mut IoSample,
completed: usize,
n_total: usize,
) {
if *n_active >= max_workers || completed >= n_total { return; }
if activation.is_full() || completed >= n_total {
return;
}
// Expect roughly 1 core of extra efficiency per worker activated in the
// last growth step (CPU-bound case); require at least CPU_SPAWN_THRESHOLD
// (20 %) of that expected gain before growing again. Scaling by the last
// step's size — not the cumulative total — keeps the bar meaningful
// regardless of how many workers are already active: growing by 8 should
// always take ~+1.6 cores to confirm, whether that's the 2nd growth step
// or the 20th.
let cpu_threshold = CPU_SPAWN_THRESHOLD * activation.last_step() as f64;
// Call both unconditionally (no `||` short-circuit): each sampler must
// advance its own window every tick, regardless of what the other one
// reports, or it would starve behind whichever signal fires first.
let cpu_wants_more = cpu_sample.do_i_activate(cpu_threshold);
let io_wants_more = io_sample.do_i_activate(io_threshold);
let io_wants_more = io_sample.do_i_activate(IO_SPAWN_THRESHOLD * activation.last_step() as f64);
if !(cpu_wants_more || io_wants_more) {
return;
}
if cpu_wants_more || io_wants_more {
activate_tx.send(()).ok();
*n_active += 1;
debug!("activated worker {}/{}", n_active, max_workers);
let grew = activation.grow(GROWTH_DIVISOR, n_total);
if grew > 0 {
debug!(
"activated {} worker(s) — {}/{} active",
grew,
activation.total(),
activation.max()
);
}
}