7 Commits

Author SHA1 Message Date
Eric Coissac 2b37e8aac4 fix(bitmatrix): explicitly compute diagonal entries for self-similarity
Release / create-release (push) Successful in 2m26s
Release / build-linux-x86_64 (push) Successful in 8m13s
Release / build-macos-arm64 (push) Failing after 30s
CI / build (pull_request) Successful in 3m21s
The pairwise matrix functions now explicitly calculate and overwrite diagonal entries using `f(i,i)`, replacing previous implicit symmetric mirroring or default values. Documentation has been updated to clarify that diagonals represent self-comparison weights, ensuring accurate self-similarity calculations. Additionally, the obikmer crate version has been bumped to 1.1.34.
2026-07-03 13:04:40 +02:00
Eric Coissac 67b4e4da53 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.
2026-07-03 13:03:31 +02:00
coissac 66ab4c6db1 Merge pull request 'feat(numa): introduce I/O sampling to prevent activation stalls' (#55) from push-ooruxnkktvvz into main
Reviewed-on: #55
2026-07-02 09:36:19 +00:00
Eric Coissac f84dd539bf feat(numa): introduce I/O sampling to prevent activation stalls
Release / create-release (push) Successful in 2m25s
Release / build-linux-x86_64 (push) Successful in 8m47s
Release / build-macos-arm64 (push) Failing after 31s
CI / build (pull_request) Successful in 3m30s
Replaces the monolithic CPU scaling threshold with separate CPU and I/O spawn thresholds. Introduces an `IoSample` struct with platform-specific byte reading and a relative throughput growth heuristic. Adds a 0.1s wall-clock guard to `CpuSample` to suppress artificial efficiency spikes, and updates `maybe_activate` to trigger worker scaling when either resource indicates headroom. Bumps `obikmer` to v1.1.33 and updates architecture documentation.
2026-07-02 10:07:22 +02:00
coissac 6378734e1c Merge pull request 'fix(obisys): remove activation guard to always update metrics' (#54) from push-vkloynurrxzu into main
Reviewed-on: #54
2026-07-01 18:34:10 +00:00
Eric Coissac b3a617cce1 fix(obisys): remove activation guard to always update metrics
Release / create-release (push) Successful in 2m26s
CI / build (pull_request) Successful in 3m35s
Release / build-linux-x86_64 (push) Successful in 8m9s
Release / build-macos-arm64 (push) Failing after 30s
Removes the `if activate` conditional in `src/obisys/src/lib.rs`, making debug logging and state updates for performance counters execute unconditionally. This ensures tracking metrics are continuously refreshed regardless of the activation threshold. Also bumps the `obikmer` dependency version.
2026-07-01 20:32:56 +02:00
coissac 2080e5e8a9 Merge pull request 'ci: fix registry auth and bump obikmer to 1.1.30' (#53) from push-zxlknspoxknt into main
Reviewed-on: #53
2026-07-01 14:20:09 +00:00
7 changed files with 495 additions and 103 deletions
Vendored
BIN
View File
Binary file not shown.
+147 -3
View File
@@ -162,14 +162,158 @@ A single `PartitionRunner` instance can be built once per command invocation
and reused across multiple `run()` calls (e.g. `merge` runs and reused across multiple `run()` calls (e.g. `merge` runs
`merge_partitions` then `pack_matrices`). `merge_partitions` then `pack_matrices`).
## Known issue: CPU-only activation signal stalls on I/O-bound stages
Observed on a real `filter` run (109 genomes, 256 partitions, 8×24-core NUMA):
`rebuild` (CPU-bound — k-mer construction) scales cleanly from 9 to 43 active
workers as `CpuSample::do_i_activate` (`obisys::lib.rs`) sees efficiency climb.
`pack_matrices` (I/O-bound — reopens and recomposes per-genome column files
into `.pbmx`/`.pcmx`) activates one extra worker then flatlines at 10/192 for
the rest of the stage, even though 256 partitions keep completing over several
minutes. This matches the documented intent (§ Adaptive mechanism — "avoids
over-provisioning ... I/O-bound ... workloads") but conflates two different
things: *"CPU is not the bottleneck"* and *"more workers would not help"*. On
storage with real queue depth (NVMe, RAID, parallel FS) the second stage could
still benefit from more concurrent workers even with flat CPU usage — a signal
the current mechanism cannot see.
A one-off artefact was also found in the same log: right after a stage
transition, `do_i_activate` produced a physically impossible spike (efficiency
~94 cores on a 192-core box) because it has no minimum-window guard — unlike
its sibling `cpu_efficiency`, which returns `0.0` if `wall < 0.1s`
(`obisys::lib.rs:260`). `do_i_activate` unconditionally overwrites
`self.wall`/`self.user_secs`/`self.sys_secs` even when the elapsed window is
too short to be meaningful, so a burst of rapid completions right after
activating a worker can divide a real CPU delta by a near-zero wall delta.
### Implemented: I/O signal + shared debounce guard
`IoSample` (`obisys::lib.rs`, alongside `CpuSample`) is fed by
`read_bytes`/`write_bytes` from `/proc/self/io` on Linux (actual bytes
submitted to the block layer — not `rchar`/`wchar`, which also count
page-cache hits, and not `ru_inblock`/`ru_oublock`, unreliable on macOS), with
a `proc_pid_rusage(RUSAGE_INFO_V4)` fallback on macOS
(`ri_diskio_bytesread`/`ri_diskio_byteswritten`, FFI only via `libc`, no new
dependency — same pattern as the existing `getrusage` bindings). Any other
target degrades gracefully to a signal that never triggers (falls back to
CPU-only activation), same pattern as `cgroup_v2_available`.
`maybe_activate` (`numa.rs`) activates a worker if *either* signal still shows
headroom, making `PartitionRunner` adapt to whichever resource is actually the
bottleneck without per-call configuration. Both samplers are called
unconditionally — no `||` short-circuit — so neither window starves behind
whichever signal fires first:
```rust
let cpu_threshold = CPU_SPAWN_THRESHOLD * activation.last_step() as f64;
let cpu_wants_more = cpu_sample.do_i_activate(cpu_threshold);
let io_wants_more = io_sample.do_i_activate(IO_SPAWN_THRESHOLD);
if cpu_wants_more || io_wants_more {
activation.grow(GROWTH_DIVISOR, n_total);
}
```
The CPU threshold is *not* the flat absolute delta it started as: it scales
with `activation.last_step()` — the number of workers activated in the last
growth step, tracked by `NodeActivation` (`numa.rs`) and updated every time
`grow()` actually grows something. Growing by 8 workers should add ~8 cores of
efficiency if the workload is truly CPU-bound; requiring only
`CPU_SPAWN_THRESHOLD` (20 %) of that expected gain confirms the growth was
useful without demanding perfect linear scaling. Scaling by the *last step's
size* rather than the cumulative total keeps the bar equally meaningful
whether it's the 2nd growth step or the 20th — a flat absolute threshold
(0.2 core) is a strong signal at 8 active workers but pure noise at 150; a
threshold scaled by the *cumulative* total instead (considered and rejected)
would have made the bar essentially impossible to clear late in the ramp,
strangling exactly the CPU-bound saturation the mechanism exists to allow.
Unlike the CPU signal (an absolute delta in cores — a bounded, portable unit),
raw I/O throughput has no natural scale across devices, so `IoSample` uses a
**relative** growth threshold instead of an absolute one:
```rust
pub fn do_i_activate(&mut self, threshold: f64) -> bool {
let elapsed = self.wall.elapsed().as_secs_f64();
if elapsed < 0.1 { return false; } // state untouched — window keeps accumulating
let n = Self::read_bytes();
let rate = n.saturating_sub(self.bytes) as f64 / elapsed;
let activate = if self.previous_rate == 0.0 {
rate > 0.0 // bootstrap: any measured throughput is signal
} else {
(rate - self.previous_rate) / self.previous_rate >= threshold
};
self.bytes = n;
self.wall = Instant::now(); // reset only on a real sample
activate
}
```
The `elapsed < 0.1s → return false without mutating state` guard was also
back-ported into `CpuSample::do_i_activate` (previously missing — source of
the ~94-core artefact above) — one fix for both problems, and it removes the
need for any arbitrary I/O-rate floor: a short/noisy window is rejected
outright rather than papered over with a hardware-dependent constant.
Both spawn thresholds (`CPU_SPAWN_THRESHOLD`, `IO_SPAWN_THRESHOLD`, module-level
`const` in `numa.rs`, both `0.2`) are a starting point, not a derived value:
`0.2` (20 % relative growth) for `IoSample` was chosen to match the CPU
threshold's *implicit* relative sensitivity (in the observed log, an 8→9
worker step raised efficiency by ~12 %) — but I/O throughput is lumpier than
CPU time (buffered writes flush in bursts), so it needs empirical validation
against a real `pack` run before being considered final.
## Known issue: ramp-up too slow, and confused with node count
The original design started `n_nodes` workers (one per node) and grew one
worker at a time. On a real `filter` run this took ~10 minutes to climb from
9 to ~40 active workers even on the CPU-bound `rebuild` stage — most of a
35-minute stage spent under-provisioned while waiting for evidence to
accumulate one worker at a time. There is no scale-down mechanism (`n_active`
only grows), so the original caution was deliberate — but a quarter of
available cores is still far from saturation, and the real risk zone (over-provisioning
a memory-bandwidth-bound stage) only shows up much later in the ramp, near
full occupancy — not at 25 %.
The fix decouples ramp speed from node *count*: both the initial size and the
growth step are a fraction of `workers_per_node` (node *size*), applied
identically on every node. A single-NUMA-node (UMA) machine ramps exactly as
fast as an 8-node one — growing by `n_nodes` per step, as first considered,
would have degenerated to "grow by 1" on UMA, reproducing the original
problem for exactly the machines that need the fix most.
```rust
// NodeActivation::grow — called both at startup (activate_initial) and on
// every CPU/IO-triggered growth step, with a different divisor each time.
let wanted = (self.caps[idx] / divisor).max(1); // INITIAL_DIVISOR=4 at startup, GROWTH_DIVISOR=8 per step
let room = self.caps[idx].saturating_sub(self.active[idx]);
let grow = wanted.min(room).min(n_total.saturating_sub(self.total));
```
This also fixed a latent correctness gap: the original single shared
`activate_tx`/`activate_rx` pair had *no* per-node addressing — sending one
activation signal woke up whichever dormant worker (from any node) happened
to win the race on that channel. `crossbeam_channel` gives no fairness
guarantee across competing receivers, so "round-robin across nodes" was an
assumption the code never actually enforced. `PartitionRunner::run` now opens
one activation channel per node (`activate_txs`/`activate_rxs`, one pair per
`NodeConfig`); `NodeActivation` (`numa.rs`) tracks how many of each node's
dormant workers have been woken and grows every node by the same amount per
step, capped by that node's remaining dormant workers and by the run's total
budget (`n_total`) — balance across nodes is now guaranteed by construction,
not incidental to channel implementation details.
## Open questions ## Open questions
- **Error handling**: `run` currently returns the first error; remaining errors - **Error handling**: `run` currently returns the first error; remaining errors
are dropped. A `Vec<E>` return would give complete diagnostics. are dropped. A `Vec<E>` return would give complete diagnostics.
- **`workers_per_node` tuning**: currently `(cpus / 8).max(3).min(8)`, calibrated - **`INITIAL_DIVISOR` / `GROWTH_DIVISOR` tuning**: currently `4` and `8`
for merge on BeeGFS. I/O-bound commands (`dump`, `select`) may benefit from (start at 1/4 of a node's cores, grow by 1/8 per step), chosen to fix an
a higher value. A per-call override could be added to the API. observed too-slow ramp — not yet validated against a real `pack` (I/O-bound)
run, where over-provisioning risk is different from the CPU-bound `rebuild`
case this was tuned against.
- **`on_done` ordering**: the runner serialises calls to `on_done` via an - **`on_done` ordering**: the runner serialises calls to `on_done` via an
internal `Arc<Mutex<C>>`. `Send` is required (the Arc clone crosses thread internal `Arc<Mutex<C>>`. `Send` is required (the Arc clone crosses thread
+1 -1
View File
@@ -1704,7 +1704,7 @@ dependencies = [
[[package]] [[package]]
name = "obikmer" name = "obikmer"
version = "1.1.30" version = "1.1.34"
dependencies = [ dependencies = [
"clap", "clap",
"csv", "csv",
+17 -3
View File
@@ -500,17 +500,26 @@ where T: Clone + Default {
} }
/// Compute a symmetric `n×n` matrix in parallel by evaluating `f(i,j)` for /// Compute a symmetric `n×n` matrix in parallel by evaluating `f(i,j)` for
/// all upper-triangle pairs. `T: Copy` avoids the `.clone()` needed for the /// all upper-triangle pairs, plus `f(i,i)` for the diagonal. `T: Copy` avoids
/// lower-triangle mirror. /// the `.clone()` needed for the lower-triangle mirror.
///
/// The diagonal is *not* generally `T::default()`: for a self-comparison,
/// `f(i,i)` is often the column's own weight (e.g. intersection-with-self —
/// see `pairwise2_matrix`), not zero. Distance finalisations that need a
/// zero diagonal (self-distance) already overwrite it explicitly.
pub(crate) fn pairwise_matrix<T>(n: usize, f: impl Fn(usize, usize) -> T + Sync) -> Array2<T> pub(crate) fn pairwise_matrix<T>(n: usize, f: impl Fn(usize, usize) -> T + Sync) -> Array2<T>
where T: Copy + Default + Send { where T: Copy + Default + Send {
let results: Vec<(usize, usize, T)> = upper_pairs(n) let results: Vec<(usize, usize, T)> = upper_pairs(n)
.into_par_iter().map(|(i, j)| (i, j, f(i, j))).collect(); .into_par_iter().map(|(i, j)| (i, j, f(i, j))).collect();
fill_symmetric(n, results.into_iter().map(|(i, j, v)| (i, j, v, v))) let mut m = fill_symmetric(n, results.into_iter().map(|(i, j, v)| (i, j, v, v)));
for i in 0..n { m[[i, i]] = f(i, i); }
m
} }
/// Same as `pairwise_matrix` but `f` returns two values that fill two /// Same as `pairwise_matrix` but `f` returns two values that fill two
/// symmetric matrices simultaneously (e.g. intersection + union for Jaccard). /// symmetric matrices simultaneously (e.g. intersection + union for Jaccard).
/// The diagonal is `f(i,i)` (e.g. a genome's kmer count intersected with
/// itself), not `T::default()` — see `pairwise_matrix` for why that matters.
pub(crate) fn pairwise2_matrix<T>(n: usize, f: impl Fn(usize, usize) -> (T, T) + Sync) -> (Array2<T>, Array2<T>) pub(crate) fn pairwise2_matrix<T>(n: usize, f: impl Fn(usize, usize) -> (T, T) + Sync) -> (Array2<T>, Array2<T>)
where T: Copy + Default + Send { where T: Copy + Default + Send {
let results: Vec<(usize, usize, T, T)> = upper_pairs(n) let results: Vec<(usize, usize, T, T)> = upper_pairs(n)
@@ -523,5 +532,10 @@ where T: Copy + Default + Send {
m0[[i, j]] = a; m0[[j, i]] = a; m0[[i, j]] = a; m0[[j, i]] = a;
m1[[i, j]] = b; m1[[j, i]] = b; m1[[i, j]] = b; m1[[j, i]] = b;
} }
for i in 0..n {
let (a, b) = f(i, i);
m0[[i, i]] = a;
m1[[i, i]] = b;
}
(m0, m1) (m0, m1)
} }
+194 -51
View File
@@ -20,7 +20,7 @@ use hwlocality::cpu::binding::CpuBindingFlags;
use hwlocality::cpu::cpuset::CpuSet; use hwlocality::cpu::cpuset::CpuSet;
#[cfg(feature = "numa")] #[cfg(feature = "numa")]
use hwlocality::object::types::ObjectType; use hwlocality::object::types::ObjectType;
use obisys::CpuSample; use obisys::{CpuSample, IoSample};
use tracing::debug; use tracing::debug;
// ── Public interface ────────────────────────────────────────────────────────── // ── Public interface ──────────────────────────────────────────────────────────
@@ -70,7 +70,10 @@ pub fn build() -> NumaSetup {
nodes.len(), nodes.len(),
nodes.first().map_or(0, |v| v.len()), nodes.first().map_or(0, |v| v.len()),
); );
return NumaSetup { pools, cpus_per_node: nodes }; return NumaSetup {
pools,
cpus_per_node: nodes,
};
} }
} }
} }
@@ -102,7 +105,9 @@ pub fn build() -> NumaSetup {
/// Silently returns on any error so the thread still runs, just unbound. /// Silently returns on any error so the thread still runs, just unbound.
#[cfg(feature = "numa")] #[cfg(feature = "numa")]
pub fn pin_current_thread(cpu_indices: &[usize]) { 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(); let mut cpuset = CpuSet::new();
for &idx in cpu_indices { for &idx in cpu_indices {
cpuset.set(idx); cpuset.set(idx);
@@ -132,7 +137,22 @@ fn build_pool(cpus: &[usize]) -> Option<rayon::ThreadPool> {
.ok() .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 { struct NodeConfig {
pool: Option<Arc<rayon::ThreadPool>>, pool: Option<Arc<rayon::ThreadPool>>,
@@ -142,19 +162,23 @@ struct NodeConfig {
/// Generic NUMA-aware runner for partition-level parallel work. /// 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. /// 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 /// Workers are pre-spawned dormant, one activation channel per node so
/// falls below `SPAWN_THRESHOLD`. This avoids over-provisioning on I/O-bound /// growth always targets a specific node rather than whichever dormant
/// or memory-bandwidth-bound workloads while saturating CPU-bound ones. /// 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 /// # Termination
/// ///
/// ```text /// ```text
/// drop(part_tx) → part_rx drains → workers exit → drop their result_tx /// drop(part_tx) → part_rx drains → workers exit → drop their result_tx
/// drop(result_tx) → result_rx closes → controller loop exits /// drop(result_tx) → result_rx closes → controller loop exits
/// drop(activate_tx) → dormant workers exit cleanly /// drop(activate_txs) → dormant workers exit cleanly
/// ``` /// ```
pub struct PartitionRunner { pub struct PartitionRunner {
nodes: Vec<NodeConfig>, nodes: Vec<NodeConfig>,
@@ -175,7 +199,8 @@ impl PartitionRunner {
ns.pools.len(), ns.pools.len(),
wpn, wpn,
); );
let nodes = ns.pools let nodes = ns
.pools
.into_iter() .into_iter()
.zip(ns.cpus_per_node) .zip(ns.cpus_per_node)
.map(|(pool, cpu_ids)| NodeConfig { .map(|(pool, cpu_ids)| NodeConfig {
@@ -189,23 +214,24 @@ impl PartitionRunner {
/// Run `f(i)` for every index in `order`. /// Run `f(i)` for every index in `order`.
/// ///
/// Workers are pre-spawned dormant and activated adaptively. A timer thread /// Workers are pre-spawned dormant and activated adaptively, per node:
/// fires a CPU-efficiency check every `TIMER_SECS` seconds; each completed /// `(workers_per_node / INITIAL_DIVISOR).max(1)` are woken immediately on
/// partition resets that timer (forcing an immediate check) and also /// every node, then `(workers_per_node / GROWTH_DIVISOR).max(1)` more per
/// triggers its own inline check. A new worker is activated whenever /// node each time the check below fires. A timer thread fires that check
/// efficiency falls below `SPAWN_THRESHOLD`. /// 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 /// `on_done(i, result, elapsed)` is called from the controller thread as
/// each partition completes — suitable for progress bars and result /// each partition completes — suitable for progress bars and result
/// aggregation. /// aggregation.
/// ///
/// Returns the first error produced by `f`, if any. /// Returns the first error produced by `f`, if any.
pub fn run<F, R, E, C>( pub fn run<F, R, E, C>(&self, order: &[usize], f: F, mut on_done: C) -> Result<(), E>
&self,
order: &[usize],
f: F,
mut on_done: C,
) -> Result<(), E>
where where
F: Fn(usize) -> Result<R, E> + Send + Sync, F: Fn(usize) -> Result<R, E> + Send + Sync,
R: Send, R: Send,
@@ -217,22 +243,28 @@ impl PartitionRunner {
return Ok(()); return Ok(());
} }
const SPAWN_THRESHOLD: f64 = 0.2;
const TIMER_SECS: u64 = 30; const TIMER_SECS: u64 = 30;
const INITIAL_DIVISOR: usize = 4;
// ── Channels ────────────────────────────────────────────────────────── // ── Channels ──────────────────────────────────────────────────────────
let (part_tx, part_rx) = unbounded::<usize>(); let (part_tx, part_rx) = unbounded::<usize>();
let (activate_tx, activate_rx) = unbounded::<()>();
// reset_tx: controller → timer ("reset the 30 s window") // 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) // 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); drop(part_tx);
let max_workers = self.max_workers(); let max_workers = self.max_workers();
let n_nodes = self.nodes.len(); let node_caps: Vec<usize> = self.nodes.iter().map(|n| n.max_workers).collect();
let f = &f; let f = &f;
let mut first_err: Option<E> = None; let mut first_err: Option<E> = None;
@@ -256,18 +288,23 @@ impl PartitionRunner {
} }
}); });
// ── Pre-spawn workers dormant, round-robin across NUMA nodes ────── // ── Pre-spawn workers dormant, grouped by node ────────────────────
for w in 0..max_workers { // Each worker listens on its own node's activation channel only.
let node = &self.nodes[w % n_nodes]; 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 prx = part_rx.clone();
let etx = event_tx.clone(); let etx = event_tx.clone();
let arx = activate_rx.clone(); let arx = arx.clone();
let pool = node.pool.clone(); let pool = node.pool.clone();
let cpu_ids = &node.cpu_ids;
s.spawn(move || { s.spawn(move || {
if arx.recv().is_err() { return; } if arx.recv().is_err() {
if !cpu_ids.is_empty() { pin_current_thread(cpu_ids); } return;
}
if !cpu_ids.is_empty() {
pin_current_thread(cpu_ids);
}
for i in &prx { for i in &prx {
let t = Instant::now(); let t = Instant::now();
let r = match &pool { let r = match &pool {
@@ -278,15 +315,17 @@ impl PartitionRunner {
} }
}); });
} }
}
// Drop controller's event_tx: event_rx closes when all workers + // Drop controller's event_tx: event_rx closes when all workers +
// timer have exited. // timer have exited.
drop(event_tx); drop(event_tx);
// ── Controller ──────────────────────────────────────────────────── // ── Controller ────────────────────────────────────────────────────
let initial_workers = n_nodes.min(max_workers).min(n_total); let mut activation = NodeActivation::new(&activate_txs, &node_caps, max_workers);
for _ in 0..initial_workers { activate_tx.send(()).ok(); } activation.activate_initial(INITIAL_DIVISOR, n_total);
let mut n_active = initial_workers;
let mut cpu_sample = CpuSample::now(); let mut cpu_sample = CpuSample::now();
let mut io_sample = IoSample::now();
let mut completed = 0usize; let mut completed = 0usize;
while completed < n_total { while completed < n_total {
@@ -295,28 +334,39 @@ impl PartitionRunner {
WorkerEvent::Completed(i, r, dur) => { WorkerEvent::Completed(i, r, dur) => {
match r { match r {
Ok(v) => on_done(i, v, dur), Ok(v) => on_done(i, v, dur),
Err(e) => { if first_err.is_none() { first_err = Some(e); } } Err(e) => {
if first_err.is_none() {
first_err = Some(e);
}
}
} }
completed += 1; completed += 1;
// Reset the 30 s timer. // Reset the 30 s timer.
reset_tx.send(()).ok(); reset_tx.send(()).ok();
// Inline check: same logic as a timer tick. // Inline check: same logic as a timer tick.
maybe_activate( maybe_activate(
&activate_tx, &mut n_active, max_workers, &mut activation,
&mut cpu_sample, SPAWN_THRESHOLD, completed, n_total, &mut cpu_sample,
&mut io_sample,
completed,
n_total,
); );
} }
WorkerEvent::TimerTick => { WorkerEvent::TimerTick => {
maybe_activate( maybe_activate(
&activate_tx, &mut n_active, max_workers, &mut activation,
&mut cpu_sample, SPAWN_THRESHOLD, completed, n_total, &mut cpu_sample,
&mut io_sample,
completed,
n_total,
); );
} }
} }
} }
// Dormant workers exit when activate_tx closes. // Dormant workers exit once every sender for their node's channel
drop(activate_tx); // is dropped — `activate_txs` holds the only ones.
drop(activate_txs);
// Timer thread exits when reset_tx closes. // Timer thread exits when reset_tx closes.
drop(reset_tx); drop(reset_tx);
}); });
@@ -335,20 +385,113 @@ enum WorkerEvent<R, E> {
TimerTick, 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( fn maybe_activate(
activate_tx: &crossbeam_channel::Sender<()>, activation: &mut NodeActivation,
n_active: &mut usize,
max_workers: usize,
cpu_sample: &mut CpuSample, cpu_sample: &mut CpuSample,
threshold: f64, io_sample: &mut IoSample,
completed: usize, completed: usize,
n_total: usize, n_total: usize,
) { ) {
if *n_active >= max_workers || completed >= n_total { return; } if activation.is_full() || completed >= n_total {
return;
}
if cpu_sample.do_i_activate(threshold) { // Expect roughly 1 core of extra efficiency per worker activated in the
activate_tx.send(()).ok(); // last growth step (CPU-bound case); require at least CPU_SPAWN_THRESHOLD
*n_active += 1; // (20 %) of that expected gain before growing again. Scaling by the last
debug!("activated worker {}/{}", n_active, max_workers); // 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_SPAWN_THRESHOLD * activation.last_step() as f64);
if !(cpu_wants_more || io_wants_more) {
return;
}
let grew = activation.grow(GROWTH_DIVISOR, n_total);
if grew > 0 {
debug!(
"activated {} worker(s) — {}/{} active",
grew,
activation.total(),
activation.max()
);
} }
} }
+1 -1
View File
@@ -1,6 +1,6 @@
[package] [package]
name = "obikmer" name = "obikmer"
version = "1.1.30" version = "1.1.34"
edition = "2024" edition = "2024"
[[bin]] [[bin]]
+93 -2
View File
@@ -266,14 +266,19 @@ impl CpuSample {
} }
pub fn do_i_activate(&mut self, threshold: f64) -> bool { pub fn do_i_activate(&mut self, threshold: f64) -> bool {
let delta_wall = self.wall.elapsed().as_secs_f64();
if delta_wall < 0.1 {
// Window too short to be meaningful — leave state untouched so it
// keeps accumulating until a real sample can be taken.
return false;
}
let n = CpuSample::now(); let n = CpuSample::now();
let delta_ru = (n.user_secs - self.user_secs) + (n.sys_secs - self.sys_secs); let delta_ru = (n.user_secs - self.user_secs) + (n.sys_secs - self.sys_secs);
let delta_wall = self.wall.elapsed().as_secs_f64();
let efficiency = delta_ru / delta_wall; let efficiency = delta_ru / delta_wall;
let activate = 0f64.max(efficiency - self.previous) >= threshold; let activate = 0f64.max(efficiency - self.previous) >= threshold;
if activate {
debug!( debug!(
"Do I activate : {} -> {} = {} Activate: {}", "Do I activate : {} -> {} = {} Activate: {}",
self.previous, self.previous,
@@ -285,7 +290,93 @@ impl CpuSample {
self.user_secs = n.user_secs; self.user_secs = n.user_secs;
self.sys_secs = n.sys_secs; self.sys_secs = n.sys_secs;
self.wall = n.wall; self.wall = n.wall;
activate
} }
}
// ── IoSample ──────────────────────────────────────────────────────────────────
/// Snapshot of process-wide block I/O (bytes read + written) + wall clock.
///
/// Same activation protocol as [`CpuSample`], but the growth check in
/// [`do_i_activate`](Self::do_i_activate) is *relative* rather than absolute:
/// raw I/O throughput has no portable scale across storage devices, unlike a
/// core count.
pub struct IoSample {
wall: Instant,
bytes: u64,
previous_rate: f64,
}
impl IoSample {
pub fn now() -> Self {
Self {
wall: Instant::now(),
bytes: Self::read_bytes(),
previous_rate: 0.0,
}
}
/// Bytes actually submitted to the block layer (read + write), summed
/// process-wide. Returns 0 if unavailable — degrades gracefully to a
/// signal that never triggers activation (CPU-only heuristic).
#[cfg(target_os = "linux")]
fn read_bytes() -> u64 {
let Ok(io) = std::fs::read_to_string("/proc/self/io") else {
return 0;
};
io.lines()
.filter_map(|l| {
l.strip_prefix("read_bytes: ")
.or_else(|| l.strip_prefix("write_bytes: "))
})
.filter_map(|v| v.trim().parse::<u64>().ok())
.sum()
}
#[cfg(target_os = "macos")]
fn read_bytes() -> u64 {
use libc::{RUSAGE_INFO_V4, getpid, proc_pid_rusage, rusage_info_v4};
let mut info: rusage_info_v4 = unsafe { std::mem::zeroed() };
let ret =
unsafe { proc_pid_rusage(getpid(), RUSAGE_INFO_V4, &mut info as *mut _ as *mut _) };
if ret != 0 {
return 0;
}
info.ri_diskio_bytesread + info.ri_diskio_byteswritten
}
#[cfg(not(any(target_os = "linux", target_os = "macos")))]
fn read_bytes() -> u64 {
0
}
/// Same protocol as [`CpuSample::do_i_activate`] (0.1 s minimum window,
/// state untouched on early return), but growth is measured relative to
/// the previous rate. `threshold` is a fraction, e.g. `0.2` for a 20 %
/// increase in throughput since the last real sample.
pub fn do_i_activate(&mut self, threshold: f64) -> bool {
let elapsed = self.wall.elapsed().as_secs_f64();
if elapsed < 0.1 {
return false;
}
let n = Self::read_bytes();
let rate = n.saturating_sub(self.bytes) as f64 / elapsed;
let activate = if self.previous_rate == 0.0 {
rate > 0.0 // bootstrap: any measured throughput is signal enough
} else {
(rate - self.previous_rate) / self.previous_rate >= threshold
};
debug!(
"Do I activate (I/O) : {} -> {} Activate: {}",
self.previous_rate, rate, activate
);
self.previous_rate = rate;
self.bytes = n;
self.wall = Instant::now();
activate activate
} }