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perf(pm): optimal — channel resolve on deps, legacy install on p0/p3#2923

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perf(pm): optimal — channel resolve on deps, legacy install on p0/p3#2923
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Optimal-hypothesis A/B from previous sweep. Stacks on PR #2920 + reverts skip_preload=true from install pipeline_deps_options to recover p3 win. Lockfile-only path keeps channel mb_fetch_with_graph for p1 win.

Expected: p1 ≈ 2.78s (PR #2920 baseline), p3 ≈ 5.95s (Plan A baseline).

elrrrrrrr and others added 30 commits May 8, 2026 21:56
…down

p1_resolve has been ~0.9s behind bun on phases bench for the past
several PRs. Pcap on prior runs measured bun opening ~260 parallel
TCP streams against registry.npmjs.org for resolve, while utoo
opened ~70 (the 64 manifests-concurrency-limit cap was at saturation).

Adding fetch-breakdown timing in ruborist showed where p1's 22s
(local Mac) actually goes:

  fetch-timings: n=2730
    sum_request   = 1089s   (88% — TCP+TLS+HTTP RTT to first byte)
    sum_body      = 138s    (11% — body download)
    sum_parse     = 2s      (0.16% — simd_json on rayon)

The dominant cost is per-request RTT, not parsing or body transfer.
The lever is the cap on concurrent in-flight requests.

This commit:

1. Adds `crates/ruborist/src/util/timing.rs` — process-wide atomic
   accumulator that records per-fetch (request_us, body_us,
   parse_us, bytes) inside both `fetch_full_manifest` and
   `fetch_version_manifest`. Reset before each preload phase, dumped
   at INFO level after preload + bfs.

2. Bumps `manifests-concurrency-limit` default 64 → 256 to match
   bun's observed working point against npmjs.org.

CI bench will validate. Expected: p1 utoo wall drops toward bun's
range (~2.3s on GHA).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Two changes after the GHA bench on the previous commit (PR #2916,
run 25559625024) showed the concurrency=256 hypothesis was wrong on
GHA's environment.

Revert concurrency 256 → 64
---------------------------

The new fetch-timing instrumentation shipped in the previous commit
caught the surprise: GHA's pcap-vs-local profile is the *opposite*
of what local Mac measurements suggested.

  metric          local Mac    GHA Linux
  avg_request     399ms        70ms      ← network MUCH faster on GHA
  avg_body         50ms        20ms
  avg_parse       730µs        266ms     ← parse 365× SLOWER on GHA

Mechanism: `parse_json_off_runtime` dispatches to `rayon::spawn`,
and rayon's pool size is `num_cpus` (= 2 on GHA ubuntu-latest).
Bumping concurrency 64 → 256 queued 256 manifest parses behind 2
rayon workers — head-of-line blocking. avg_parse jumped from ~10ms
to 266ms wall, dragging p1 utoo wall from 3.10s up to 3.33s.

Restore manifest-bench
----------------------

Brought back `crates/manifest-bench` (originally landed in the
post-#2818 driver hunt, dropped in af714eb once #2818 graduated).
It's a single-binary HTTP-only fetch tool that strips out the
ruborist pipeline (no BFS, no dedup, no parse, no project cache,
no lockfile write) — fires `GET <registry>/<name>` in parallel
and reports the same diag shape as the new `p1-breakdown` lines.

Goal: separate the network ceiling from the resolver pipeline so
the next round of p1 experiments (parse offload, partial parse,
dedicated parse pool, etc.) can be evaluated against a stable
"pure network" baseline.

Knobs (unchanged from the original drop):
  --concurrency N    sweep without rebuilding utoo
  --reps N           run same workload back-to-back
  --single-version   use /<name>/latest (smaller bodies)
  --user-agent X     UA-fingerprint experiments
  --http1-only       H2 vs H1 toggle
  --accept X         override Accept header

Same TLS stack as ruborist (rustls + aws-lc-rs, native roots).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
…inux

build-linux now also builds + uploads `manifest-bench` when a phases
bench is going to run (label or dispatch). bench-phases-linux
downloads the binary and runs it after the regular phase-isolated
benchmark.

Sweep mirrors the original (#2818-era) wire-in:

  concurrency: 32 / 64 / 96 / 128 / 192 / 256  (HTTP/1.1, full manifest)
  protocol:    H1 vs H2-negotiate  (cap=128)
  endpoint:    full vs `/<name>/latest`  (cap=128, smaller bodies)
  UA:          default vs `Bun/1.2.21`  (cap=128)

Output goes to /tmp/pm-bench-output/manifest-bench-npmjs.log and
ships in the existing pm-bench-logs-linux artifact — no PR comment
surface (the headline phases bench comment stays the same).

Why now: the new ruborist `p1-breakdown` instrumentation showed
sum_parse on GHA can dominate when concurrency is bumped (256:
sum_parse 728s vs sum_request 193s). To attribute the bun-vs-utoo
gap on p1_resolve we need a "pure HTTP" baseline that strips out
ruborist's parse / BFS / dedup / lockfile path. manifest-bench is
that baseline: same TLS stack as ruborist (rustls + aws-lc-rs,
native roots), no resolver pipeline.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
CI fetch-breakdown on GHA (run 25562552058, conc=64) showed parse
queueing on rayon dominates the gap to manifest-bench's pure-HTTP
baseline:

  manifest-bench (pure HTTP, conc=64): 2.12s wall
  utoo p1 (full ruborist):             3.10s wall  ← +1.0s overhead
  ↑ sum_parse 95s vs sum_request 95s, parse 50% of work-time
  ↑ avg_parse 30ms wall vs ~5ms actual CPU — the 25ms extra is rayon
    queue wait

Mechanism: 64 concurrent tasks all dispatching parse to rayon's pool
(size = num_cpus = 2 on GHA). Queue depth grows to ~32 per worker.
Each parse waits 25ms+ in queue before running its 5ms of CPU work.

Round 1 fix: inline parse, drop the rayon hop. simd_json on a tokio
worker thread is fast (~5ms for 115KB JSON), and the tokio runtime's
cooperative budget naturally rebalances CPU across the 64 tasks.

Expected on next CI:
- avg_parse drops from 30ms wall → ~5-10ms wall (close to CPU-only)
- preload_wall drops from 5.4s → ~3.5-4s for cold runs
- p1 hyperfine wall drops from 3.10s → 2.3-2.5s, narrowing the gap
  to manifest-bench's 2.12s ceiling

If parse becomes the new bottleneck (CPU-bound), next round could
look at partial parse / lazy field access. If wall doesn't drop,
hypothesis is wrong and we look elsewhere (BFS, dedup, lockfile).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Round 1 (inline parse) reverted on data: GHA showed +0.37s p1
regression because parse blocked tokio runtime workers, dropping
eff_parallel 42 → 35 even though per-fetch work-time fell. avg_request
went up from 35ms → 52ms — symptomatic of socket reads being delayed
by the parsing task on the same worker.

  metric           round 0 (rayon)  round 1 (inline)
  p1 wall          3.27s            3.64s   ⚠️ +0.37s
  avg_parse        30ms (queued)    300µs   ✓
  avg_request      35ms             52ms    ⚠️ +17ms (worker contention)
  eff_parallel     42               35      ⚠️

Round 2 attempts the third option: `tokio::task::spawn_blocking`.

  - rayon's pool was too small (num_cpus = 2 on GHA) — 64 concurrent
    parses queued behind 2 workers, parse wall 30ms.
  - inline parse held tokio worker hostage during simd_json call,
    starving in-flight socket reads.
  - tokio's blocking pool has a much larger default cap (512), so 64
    concurrent parses never queue. Unlike rayon there's no contention
    with the install path's parallel-write rayon usage. Unlike inline
    the tokio runtime workers stay free to drive network I/O.

Expected on next CI:
  - avg_parse drops to ~5-10ms wall (close to CPU floor, no queue)
  - avg_request stays ~35ms (workers free for I/O)
  - eff_parallel returns to ~50, possibly higher
  - p1 wall drops toward manifest-bench's 2.10s ceiling

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Round 2 moved parse_json_off_runtime off rayon (-0.11s p1). But
fetch-breakdown still showed avg_request 41ms vs round 0's 35ms,
hinting at a second source of rayon contention.

Found it: `extract_core_version_off_runtime` is also on
`rayon::spawn`. On npmjs.org's `!supports_semver` path EVERY fetch
resolves through `resolve_via_full_manifest`, which fetches the
full packument once per package name (deduped via inflight_full)
and then calls `extract_core_version_off_runtime` per (name, spec)
to materialize the chosen version into a `CoreVersionManifest`.

So per fetch we hit rayon TWICE — once for the JSON parse (round 2
moved to spawn_blocking), and once for `get_core_version` (still on
rayon). The second hop has the same head-of-line blocking signature
as the first: 64 concurrent resolves dispatching to a 2-thread
rayon pool.

Round 3: move extract_core_version_off_runtime to spawn_blocking
for the same reasons. The work is JSON lazy-reparse (`raw_json`
sub-tree decoding) — genuinely blocking, well-suited for tokio's
blocking pool.

Expected: utoo p1 wall drops further toward manifest-bench's 2.10s
ceiling. avg_request should fall back from 41ms → ~35ms (rayon
contention removed from the fetch task's await chain).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Two changes for round 4 of p1 optimization:

1. Revert `extract_core_version_off_runtime` from spawn_blocking back
   to rayon::spawn (round 3). Within-run measurement showed +0.42s
   regression vs utoo-next (round 2 was +0.11s). Likely cause: this
   function is called per (name, spec), so multi-spec packages call
   it 2-5x per fetch. spawn_blocking's per-dispatch overhead exceeds
   rayon queue savings at this multiplier.

2. Add `serialize_us` and `cache_export_us` to the p1-breakdown line
   so we can attribute the remaining gap. Currently:

     manifest-bench wall:     2.10s   (pure HTTP ceiling)
     utoo p1 wall (round 2):  3.16s
     gap:                     1.06s

   We have:
     preload_wall  ≈ 2.7s   (logged)
     bfs_wall      ≈ 0.3s   (logged)
     serialize_us  ?
     cache_export_us ?      ← suspected: full manifest deep-clone
                              into ProjectCacheData for ~2730 entries

   Next round will have data to choose between attacking serialize,
   cache export, or the BFS loop body.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Round 4 measured serialize_us = 15ms and cache_export_us = 34ms — both
tiny — confirming the 1s gap from manifest-bench (utoo p1 = 3.16s vs
mb wall = 2.10s) is not in post-build code.

Per-fetch math also pointed at main-loop bookkeeping:

  manifest-bench: eff_parallel = 52 (sum_work 111s / wall 2.14s)
  utoo preload  : eff_parallel = 43 (sum_work 120s / wall 2.85s)

Same conc=64 cap, but utoo loses 9 effective slots — most likely
the main loop's serial bookkeeping (dedup hash insert, format!
key, extract_transitive_deps, queue push, 3-4 receiver events)
holds the flow between futures.next() returning and the next
fetch dispatch.

This commit splits the main loop into two timed segments:

  preload_loop_dispatch_us: time spent in the `while in_flight <
                            concurrency` block — popping pending,
                            dedup check, futures.push.
  preload_loop_result_us:   time spent processing each completed
                            future — extract_transitive_deps,
                            pending.extend, on_manifest.

If dispatch+result sum approaches preload_wall, the main loop is
the bottleneck and we need to either (a) split processing onto a
dedicated task, or (b) use unbounded futures with a downstream
consumer. If they're small, the gap is elsewhere (per-task
overhead in resolve_package's inflight gates).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Round 5 main-loop instrumentation showed the preload main loop
itself is fast (15-25ms total dispatch+result). The 0.8s gap from
manifest-bench's 2.10s wall lives INSIDE the spawned fetch tasks.

Per-fetch wall (warm runs):
  measured: avg_request 30ms + avg_body 6ms + avg_parse 2.5ms = ~38ms
  derived:  preload_wall 2.4s × eff_parallel(43) / 2730 = 38ms
  delta:    ~12ms unaccounted per task

That 12ms is `extract_core_version_off_runtime` queueing on rayon's
2-thread pool. extract is called per (name, spec) — for ant-design
that's ~3000+ calls. With pool=2 and 64 concurrent fetches each
dispatching extract, the queue depth grows; each task waits its
turn before extract returns.

Bump rayon pool to `max(num_cpus, 8)` for non-Windows. Sizing the
pool above the CPU count for short blocking JSON ops (parse + extract)
replaces FIFO queueing with parallel dispatch. Real CPU contention
is bounded by num_cpus (the kernel scheduler still gates), so the
extra pool threads just hold ready-to-run dispatches in parallel
rather than serialised in a queue.

Why not just spawn_blocking (round 3 attempt): tokio's blocking pool
defaults to 512 threads, but its per-dispatch overhead was higher
than rayon's even when queueing — round 3 regressed by 0.5s.

Expected: extract queue wait drops from ~12ms to ~1-2ms wall, p1
preload_wall narrows toward manifest-bench's 2.10s.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds `BuildDepsOptions::skip_preload` so callers without a pipeline
consumer (utoo deps / package-lock-only) can drop the up-front
preload phase entirely. BFS now batches prefetch per level across
the whole frontier, then runs the existing sequential
process_dependency walk against the warmed cache.

For install paths (Context::pipeline_deps_options), skip_preload
stays false so PackageResolved events still feed the
download/clone pipeline.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds resolver::fast_preload, a manifest-bench-style flat
FuturesUnordered over service::manifest::fetch_full_manifest. It
warms MemoryCache (both full_manifests and version_manifests slots)
synchronously after each fetch, so the BFS phase is pure cache-hit:
no rayon hop on extract_core_version, no OnceMap gates, no
DiskManifestStore writes, no PackageResolved events.

Wired into service::api::build_deps: when the caller asks to skip
preload (Context::build_deps for `utoo deps`) and there's no warm
project cache, fast_preload runs ahead of build_deps_with_config.
Install paths still go through preload_manifests so the pipeline
keeps its early-start signal.

Also reverts the per-level prefetch I added in 394f6c9 — with
fast_preload pre-warming everything, BFS doesn't need its own
prefetch wave.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
v1 of fast_preload called settle_spec inline on the tokio worker —
each settle ran simd_json::to_borrowed_value over the full
manifest's raw bytes (5–10ms per spec) right on the runtime
thread. CI showed it starved sibling fetches: avg_request rose
+3ms, avg_parse jumped 5→11ms, p1_resolve regressed +1.0s vs the
preload+BFS baseline (4.0s vs 3.0s).

Fix: route every settle through extract_core_version_off_runtime
(the same rayon::spawn helper the BFS path uses), and merge fetch
and settle completions into a single FuturesUnordered so
backpressure on either side throttles the other. Sibling specs
that arrived during a fetch are now stashed by name (HashMap, not
linear scan), then dispatched as their own settle futures when
the fetch lands.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Standalone manifest-bench HTTP-only sweep (npmjs, h1) shows wall
bottoming at concurrency=96 (1817ms) — earlier 256 regression was
caused by rayon-queued parses behind 2 workers, no longer relevant
since fetch parse is on spawn_blocking and settle is rayon-dispatched
off the runtime.

fast_preload's wave-shaped transitive walk currently runs at
eff_parallel ~35 against the 64 cap because pending refills lag
settles; raising the cap to 96 gives headroom for sustained
in-flight on the deep waves without crossing the npmjs per-IP
tail-latency cliff that conc 128+ trips.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
… path

`UnifiedRegistry::resolve_version_manifest`'s first cache check
(service/registry.rs:347) keys on `(name, spec)` — the original spec
string the caller passed, e.g. `^4.0.0`. settle_future was only
populating `(name, resolved_version)` (e.g. `4.17.21`), so on every
BFS edge for `lodash@^4.0.0`-style specs the warm path missed and
fell into the OnceMap inflight gate + `resolve_via_full_manifest`
re-walk before recovering the manifest from the
`(name, resolved_version)` slot we'd already set.

Now settle writes both keys so BFS hits the early-return at
service/registry.rs:347 with no further dispatch. Saves ~1
OnceMap+resolve_target_version round-trip per unique (name, spec)
the BFS encounters (≈3000 calls on ant-design-x).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Previous fast_preload (v2) dispatched primary settles to rayon as
separate FuturesUnordered futures. CI breakdown showed
eff_parallel ~44 against the conc=96 cap — the wave-shaped
transitive walk was held back by settle dispatch RTT: each fetch
landed → primary settle queued → settle popped → only then did
`pending` get transitive deps and fill the next dispatch wave.

v3 folds the primary settle into the fetch task itself via
`tokio::task::spawn_blocking`. The fetch task does the network
round-trip and the primary version-extract on the same blocking
pool slot, then returns with the resolved CoreVersionManifest
attached. Main loop pulls one Fetched event, immediately extends
`pending`, no second `next().await` to wait through the queue.

Sibling specs (rare; same name, different range) still go through
the rayon settle_future path so the primary path stays lean.

Carries primary_spec through FastEvent so the fused path can
populate both `(name, primary_spec)` and `(name, resolved_version)`
cache slots — preserves the 6455852 BFS fast-path win.

FetchOutcome enum replaces by-value FetchManifestResult to avoid a
full FullManifest clone (HashMap+Vec) per fetch event.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
…json

The fast_preload hot path was paying TWO simd_json passes per
manifest:
  1. fetch_full_manifest's parse_json_off_runtime did a typed
     simd_json::serde::from_slice<FullManifest> (envelope + IgnoredAny
     visitor on `versions` keys, ~3-5ms on a 100KB body).
  2. Primary settle re-parsed the same raw bytes with
     simd_json::to_borrowed_value (~5-10ms) to extract one version's
     subtree.

Both passes went through simd_json's Tape constructor — duplicated
work. CI showed avg_parse 5-7ms × 2700 fetches = 14-19s of CPU sum
on 2-core GHA, where the spawn_blocking pool's overlapping schedule
masked some of the cost but not all.

Adds `service::manifest::fetch_full_manifest_with_settle`: same HTTP
+ retry + ETag machinery as `fetch_full_manifest`, but the parse
step does ONE `to_borrowed_value` and extracts:
  * envelope (`name`, `dist-tags`, `versions` keys) into FullManifest
    manually (no typed serde), and
  * the resolved version's subtree as a typed CoreVersionManifest
    (serde-deserializing that single subtree via the borrowed value).

fast_preload's fetch task switches to this entry point — primary
settle is now a free byproduct of the fetch parse, not a separate
`to_borrowed_value` pass. Sibling specs (same name, different
range) still go through the rayon settle_future path.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
After 671ac98's combined-parse fetch path eliminated the
double simd_json pass, the spawn_blocking pool's contention
ceiling rose enough that bumping concurrency past 96 no longer
queues parses behind 2-core CPU. manifest-bench's most recent
good-network sweep on GHA showed conc=128 hitting 1500ms vs
conc=96 at 1566ms — small but real headroom for fast_preload's
late-wave saturation now that initial waves fill faster.

Risk: on slower-network runs (npmjs per-IP throttle), conc=128
widens p99. Earlier conc-sweep data was mixed — accepting that
variance for the average-case improvement.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
542d7f1's conc=128 bench landed in a slow-network run (mb best
2010ms vs 1500ms in the prior good-network run; bun also bumped
to 2.14s vs 1.83s). Adjusted gap to mb best stayed flat (~700ms
either way), so conc=128 didn't beat 96 across runs.

Picking 96 as the conservative default: at-or-near best on every
GHA run we've measured, never the worst, and leaves headroom for
npmjs's per-IP throttling to absorb without compounding p99.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
…preload)

Adds resolver::mb_resolve module + service::build_deps_mb entry point
as a parallel-track alternative to fast_preload, structured to
match manifest-bench's main-loop shape as closely as correctness
allows. Hypothesis under test: fast_preload's eff_parallel caps at
~50/96 because the FastEvent enum match + cache writes + sibling
deferred bookkeeping in the main loop competes with tokio runtime
workers for the 2 CPU cores on GHA, stalling socket I/O drive.

mb_fetch pushes ALL per-fetch work into the spawned future itself
(including cache writes), so the main loop is reduced to:

  while let Some(deps) = futs.next().await {
      pending.extend(deps);
      refill_to_cap(...);
  }

Sibling specs (multiple ranges on same package) are NOT deferred at
queue level — racing fetches for the same name both proceed. The
race converges naturally: first fetch to land populates
full_manifests, subsequent racers find the cache hit on entry and
short-circuit to a sibling-style settle. Wastes ~5-50 network
requests in real workloads but eliminates the HashMap probe + drain
overhead from the hot loop.

Wired in via UTOO_RESOLVE=mb env var:
- Context::build_deps (utoo deps) routes through build_deps_mb
- pipeline::resolve_with_pipeline (utoo install) also routes
  through it; pipeline workers still start but don't pipeline
  during fetch (mb_fetch emits no PackageResolved events) — install
  becomes phase-sequential, useful for resolve-phase A/B.

bench script enables UTOO_RESOLVE=mb so CI measures the new path
against existing baselines (utoo-next/utoo-npm/bun ignore the env
var). Comment the export line to A/B back against fast_preload.

Old fast_preload + UnifiedRegistry paths untouched.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
v1/v2 ran parse work in spawn_blocking inside each fetch future,
which competed with tokio runtime workers for the 2 GHA cores. CI
showed eff_parallel capped at 47/96 vs manifest-bench standalone's
75/96 on the same box. Hypothesis: parse CPU starves socket drive.

v3 separates the two phases:

* PHASE 1 — `mb_style_pure_fetch` is a structural copy of
  `manifest-bench`'s main loop: future body does ONLY GET + body
  recv, refill 1-for-1 on completion. Zero per-future CPU work, so
  tokio runtime workers retain full CPU for socket drive.

* PHASE 2 — bulk rayon par_iter parse: for each body, parse
  `FullManifest` envelope via simd_json::to_borrowed_value, resolve
  every queued spec for this name against the just-parsed manifest,
  populate cache slots, collect transitive deps. Runs off the
  tokio runtime entirely (spawn_blocking → rayon par_iter).

Phases alternate until pending exhausted. Typical project: 3-5
iterations as the dep tree fans out wave by wave.

The point of the split is the `phase1_http_wall` trace — measured
in isolation from any parse work, it should match manifest-bench's
standalone wall (~1.5-2.0s for 2733 names @ conc=96). If it does,
the remaining gap to mb is concentrated in phase 2 work, which is
inherent to discovering transitive deps from a non-flat name list.

Tracing per iteration:
  p1-breakdown mb_fetch iter=N phase1_http_wall=Xms n=Y bytes=Z
  p1-breakdown mb_fetch iter=N phase2_parse_wall=Xms settles=Y new_transitives=Z
  p1-breakdown mb_fetch total_wall=Xms iters=Y

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
v3 dropped the (name, spec) HashSet from v1/v2 thinking name-level
dedup via done_names was sufficient. It wasn't: sibling-settle's
extract_transitive can re-introduce specs we've already settled
(peer/optional dep cycles trivially trigger this), so the outer
while-loop never terminated.

CI 25589397823 hung on `Run phase-isolated benchmark · npmjs` for
~25 min before being cancelled — the bench's first utoo p1_resolve
hyperfine run got stuck in an infinite settle loop.

Fix: maintain `seen_specs: HashSet<(String, String)>` across all
iterations; filter both initial seed and every wave of new
transitives through it before extending pending_specs.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
New crate `crates/preload-bench/` is a fully-standalone bench that:
* Uses the SAME HTTP setup as `manifest-bench` (own reqwest::Client
  built per rep with aws-lc-rs TLS, pool_max_idle_per_host(256), no
  proxy, default DNS, no retry, h1_only).
* Discovers names by walking transitive deps from a package.json
  root — instead of consuming a flat name list like manifest-bench.
* Per-future does GET + body recv + spawn_blocking parse → returns
  transitive deps → main loop refills on completion.
* No dependency on ruborist or any utoo internals (own simd_json,
  own dedup, own everything).

The point: prove (or disprove) that a fully ruborist-independent
streaming preload can hit standalone manifest-bench's wall on the
same workload. ruborist's path runs at ~2.18s for ant-design's
~2700 names; manifest-bench standalone runs the same workload at
~1.6s. The gap could be in any number of things — DNS layer, retry,
pool config, parse-CPU contention, registry single-flight gates.
preload-bench eliminates all of those simultaneously so we can read
the wall directly.

Wired into bench-phases-linux: builds + uploads preload-bench
binary alongside manifest-bench, then runs a conc=64/96/128 sweep
against the same project after the standalone manifest-bench sweep.

bench script reverts UTOO_RESOLVE=mb so utoo runs default
fast_preload — gives a third datapoint (utoo wall on integrated
path) alongside manifest-bench (HTTP-only ceiling) and preload-bench
(streaming-with-walk ceiling).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
…y path

Step 1 of staged service-layer ablation. Rewrites mb_resolve as a
fully self-contained streaming preload mirroring preload-bench's
loop shape verbatim, but living inside ruborist so it can populate
MemoryCache for the BFS phase.

Bypasses every other ruborist service layer:
  * service::http::get_client — own reqwest::Client built per call,
    no global LazyLock, no shared_resolver dns layer, no
    connect_timeout, pool_max_idle_per_host(256).
  * service::manifest::fetch_full_manifest_with_settle — own GET +
    body.bytes() + spawn_blocking(simd_json::to_borrowed_value),
    no RetryIf, no FETCH_TIMINGS.
  * service::registry::UnifiedRegistry — no OnceMap, no
    ManifestStore, no EventReceiver.

Only service::* touched is MemoryCache writes (DashMap inserts) so
BFS has data to read from.

PM is unaware: dispatch happens entirely inside
service::api::build_deps when skip_preload=true and no warm cache.
Removes the previous UTOO_RESOLVE=mb env-var gating from
pm::helper::ruborist_context::Context::build_deps and
pipeline::resolve_with_pipeline. Removes the now-unused
service::api::build_deps_mb sibling entry point.

Expected: utoo p1_resolve drops from ~2.67s toward preload-bench's
~2.57s (or better since ruborist fetches fewer names than
preload-bench). The remaining gap to mb's ~1.99s would isolate
incremental layer effects we add back next:
  - tokio runtime config / cooperative scheduling
  - reqwest::Client provider differences (TLS, DNS)
  - cache layer (DashMap vs DiskManifestStore reads on the cold path)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
…mb_fetch

Step 2 of staged service-layer ablation. Targets the two gaps
left after step 1:

1. mb_fetch (in ruborist): 2300ms / 2735 = 0.84 ms/name
   manifest-bench (standalone): 2010ms / 2735 = 0.72 ms/name
   ~290ms gap on same workload, same conc.

2. BFS phase: 305ms wall against a fully-warm MemoryCache.
   Origin unclear — could be graph mutations, repeated cache
   lookups via the inflight gate, or event dispatch.

Changes:

* TLS provider — adds rustls (aws-lc-rs) + rustls-native-certs to
  non-wasm-non-macos targets. mb_resolve's `build_mb_client` now
  uses `use_preconfigured_tls(aws_lc_rs)` matching
  preload-bench / manifest-bench exactly. The reqwest crate's
  `rustls-tls-native-roots` feature on Linux still bundles ring
  for service::http's global client; the two providers coexist.

* mb_fetch instrumentation — per-future `wall_us` (network +
  parse + cache writes) and `net_us` (network only) reported in
  the trace line as `eff_par_full`, `eff_par_net`, `avg_wall`,
  `avg_net`. Same shape as manifest-bench's `avg_conc` so we can
  compare directly.

* BFS instrumentation — splits run_bfs_phase wall into:
    - `collect_us`: collect_unresolved_edges sum
    - `resolve_us`: process_dependency .await sum
    - `event_us`: post-resolve event dispatch (Resolved /
      PackagePlaced / Reused / Skipped) sum
  Plus `levels` and `edges` counters. Trace line lets us
  attribute the 305ms.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Step 3 of staged service-layer ablation. Targets the 305 ms BFS
phase observed against a fully-warm MemoryCache — 100 % attributed
to process_dependency.await sum (graph mutations) per d9fb207's
new bfs instrumentation.

Adds:
* `process_dependency_with_resolved` in builder.rs — sync variant
  of process_dependency for the registry-resolved case. Skips
  spec-routing (only Registry handled), skips resolve_registry_dep
  (resolved is the parameter), skips override re-resolve. Reuses
  existing helpers (find_compatible_node, create_package_node,
  add_edges_from, mark_dependency_resolved, update_node_type_from_edge).
* `mb_fetch_with_graph` in mb_resolve.rs — folded streaming preload
  + graph build. Each fetch result triggers inline
  process_dependency_with_resolved for every parent edge waiting
  on (name, spec). New nodes' edges feed back into pending /
  edge_targets, so the walk continues streaming-style.
  CPU work (graph mutations, ~305 ms total) overlaps with network
  IO (mb_fetch's wall ~2.4 s).

Wires `service::api::build_deps` to use mb_fetch_with_graph for
the lockfile-only path (skip_preload + cold cache). The
follow-up build_deps_with_config still runs to handle any
non-registry edges left unresolved (workspace / git / http /
file); on registry-only workloads it's near no-op.

Install path unchanged — pipeline_deps_options keeps preload +
PackageResolved early-start signal for tgz download.

Expected: utoo p1 wall drops from ~2.76 s toward mb_fetch wall +
serialize ≈ 2.4-2.5 s on good network. Tracing line:
  p1-breakdown mb_fetch_with_graph wall=Xms ok=N fetch=N
  settle=N sum_wall=Xms sum_net=Xms sum_graph=Xms avg_net=Xus
  eff_par_full=N.N eff_par_net=N.N unresolved_targets=N

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
c02bb15 had unresolved_targets=583 in trace — `enqueue_node_edges`
was unconditionally pushing (parent, edge_id) into edge_targets
without checking if the (name, spec) was already cached. When a
later transitive's edge referenced an already-fetched (name, spec),
no fetch result would land to drain that bucket — the parent edges
sat unresolved, potentially missing packages from the lockfile.

Fix: enqueue_node_edges now checks cache.get_version_manifest
first. Cache hit → process_dependency_with_resolved inline (with a
work_stack to recurse into newly-Created nodes' edges). Cache
miss → original behavior (stash in edge_targets, push to pending).

Side effect: more inline graph mutation work in the seed phase
(workspace + root edges that hit warm cache from previous specs in
the same root). Should reduce the number of fetch-result events
that need to do graph mutations downstream, since orphan edges no
longer accumulate.

Targets the correctness bug from c02bb15 trace; perf impact TBD.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The 700ms gap between utoo p1 (folded mb_fetch_with_graph) and
manifest-bench standalone needs network-layer evidence. Same
workload, same conc, same network → why does utoo wall trail by
700ms when per-fetch latency is matched (avg_net=53us = mb p50=40us
ish)?

Hypotheses to test via pcap diff:
* Fewer concurrent TCP streams in flight at any moment (utoo's
  main loop CPU steals tokio dispatch capacity → in-flight count
  drops below conc cap)
* More TLS handshakes (utoo's connection pool isn't reusing as
  effectively as mb's per-rep fresh client)
* Larger inter-packet gaps per stream (utoo's runtime pauses mid
  download)
* Different concurrent-stream-time profile (wave shape)

Adds two captures at end of pm-bench-pcap.sh:
  manifest-bench-c96 — flat lockfile-derived names @ conc=96
  preload-bench-c96  — transitive walk @ conc=96 (matches utoo's
                       walk shape, but no graph build)

Each captured with the same tcpdump + iostat as the existing
utoo / utoo-next / bun captures. analyze_pcap globs *.pcap so the
new files get the same TCP signal extraction (zwin / retx /
dup_ack / per-stream gap p50/p99/max / distinct streams).

Workflow: downloads manifest-bench-linux-x64 +
preload-bench-linux-x64 artifacts (built by build-linux's
benchmark-label conditional steps) into the pm-bench-pcap-linux
job env so pm-bench-pcap.sh can find them.

Trigger: workflow_dispatch with target=pm-bench-pcap.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Previous pm-bench-pcap artifact was 2GB (raw .pcap files for every
PM × phase × bench), making the round-trip download impractical
just to read JSON metrics. Adds a separate `pm-bench-pcap-summaries`
artifact containing only the *.json / *.log / *.iostat.txt / dns.txt
files — KB scale, downloads in seconds.

Raw pcap artifact is preserved for cases where we want to re-run
tshark with different filters.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The pm-bench-pcap artifact is ~2 GB (pcap binaries dominate). gh
run download keeps timing out before completion. Two fixes:

1. New `pm-bench-pcap-summaries` artifact uploads only the JSON
   summaries + .log + iostat.txt + dns.txt (small, fast download).
   The full pcap artifact stays for deep inspection when needed.

2. End of pm-bench-pcap.sh prints a tab-separated comparison
   table (name, wall_s, packets, streams, zwin, retx, dup_ack,
   gap_p99_us, gap_max_us) to stdout, so the data is visible in
   the CI run log without downloading anything.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
…raph

The pcap evidence (utoo-resolve zwin=71 vs mb-c96 zwin=49) confirmed
main loop CPU was starving tokio runtime workers from polling
sockets. Inline graph mutations (sum_graph=450ms across the fetch
loop) blocked the worker between awaits, so TCP receive buffers
filled and the server paused sending — directly extending wall.

This refactor:
* Spawns `graph_worker` as a separate tokio task (gets its own
  runtime worker thread on multi-thread runtime). Owns the
  DependencyGraph + edge_targets + seen_specs.
* Main loop owns FuturesUnordered + body_cache + dispatch state.
  No graph mutations on this path.
* mpsc channels: main → graph (FetchEventMsg, just the name —
  cache writes already in the future), graph → main (Vec<Dep>
  new pending specs to extend the fetch queue).
* `tokio::select!` with `biased` drains specs first to unblock
  fetch dispatch.
* `in_flight_graph` counter tracks outstanding messages to graph
  worker — termination = futs empty + in_flight_graph == 0.

Function signature changed: takes `mut graph: DependencyGraph` by
value, returns `(DependencyGraph, MbFetchStats)` since the worker
task needs ownership of the graph (can't borrow across spawn).
api.rs caller threads the graph through.

Expected: zwin drops back toward mb's ~49 (no more main loop
starvation), eff_par_net climbs from 56 toward mb's 72, wall
saves ~200ms.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
elrrrrrrr and others added 5 commits May 9, 2026 23:54
Plumb the PipelineReceiver through the folded mb_fetch_with_graph path
so install (`utoo install`) gets the same channel-separated fetch + graph
architecture as `utoo deps`, with download/clone pipelines starting as
early as the legacy preload+BFS path:

- mb_fetch_with_graph now takes Arc<R: EventReceiver + 'static>; main
  loop emits PackageResolved on each fetch land (looked up via cache
  with the new FetchOutcome::primary_spec), graph_worker emits
  PackagePlaced on ProcessResult::Created.
- service::api::build_deps wraps the caller-supplied receiver in Arc
  once and shares it between mb_fetch_with_graph and
  build_deps_with_config; adds + 'static bound on R.
- pipeline_deps_options sets skip_preload=true so install routes
  through the same folded path as the lockfile-only command.

CI will validate that p1 resolve continues at/below 2.5s while
p0_full_cold and p3_cold_install do not regress (download + clone
pipelines remain saturated via emitted events).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Previously spawn_fetch / spawn_settle used the raw dep key as both
the registry path segment and the cache lookup key. For an npm-alias
dep like \`\"ms\": \"npm:raw-body@2.1.3\"\` this hit
\`registry/ms\` instead of \`registry/raw-body\`, parsed ms's manifest
against \`npm:raw-body@2.1.3\`, and ultimately installed the real ms
into \`node_modules/ms/\` rather than raw-body. e2e
\`utoo-pm.sh:466\` (\"top-level ms should be raw-body\") caught this
on d1cf53e.

Fix:
- spawn_fetch / spawn_settle call \`normalize_spec\` to split out the
  real package name + spec; URL hits \`registry/{real_name}\` and the
  combined parse runs against \`real_spec\` so version resolution sees
  the right manifest envelope.
- Cache writes go under both keys: the original
  \`(alias_name, alias_spec)\` so \`graph_worker\` finds the manifest
  via \`edge_targets\`, and the normalized
  \`(real_name, resolved_version)\` for direct-dep dedup.
- Main loop dedup state (in_flight_names / deferred_by_name /
  body_cache) keys by real_name so two distinct aliases pointing at
  the same registry package share dedup; deferred entries store
  \`(alias_name, spec)\` so the drain spawns spawn_settle with the
  correct cache key.
- Adds \`real_name\` to FetchOutcome so the deferred-drain step can
  look up by real name without re-normalizing.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
GHA ubuntu-latest is a 2-core runner; tokio's default worker_threads
= num_cpus = 2. The install hot path multiplexes four concurrent task
families on those workers:
- mb_fetch_with_graph main loop (drives sockets + FuturesUnordered)
- graph_worker (\`tokio::spawn\`, CPU-heavy)
- pipeline download workers (PackageResolved → tarball fetch)
- pipeline clone workers (PackagePlaced → hardlink/clonefile)

Under that load, graph_worker can monopolize a worker thread for tens
of ms at a stretch, starving the main loop's socket polling. The
symptom is a wave-shape collapse (eff_par_full 73-77 → 40, mb_fetch
wall 4-6s → 10s+) that pushes p0_full_cold tail by 3-5s on the
affected run.

Floor worker_threads at \`max(num_cpus, 4)\` so the runtime always has
headroom to keep the resolve hot path on its own worker even when
the install pipeline saturates the others. No-op on 4+ core machines.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
graph_worker is pure CPU + channel IO; on a multi-thread tokio runtime
it sat on a worker thread that the install pipeline (download + clone
+ extract) and the resolve main loop were also competing for. Under
the 2-core GHA ubuntu runner that contention produced the eff_par_full
collapse (73-77 → 40) and 4-6s → 10s+ mb_fetch wall on the p0/p1
outlier runs.

Move it to \`tokio::task::spawn_blocking\`:
- Convert graph_worker from \`async fn\` to sync \`fn\`; channel IO
  uses \`mpsc::Receiver::blocking_recv\` and \`mpsc::Sender::blocking_send\`,
  which are tokio-supported when called outside an async context.
- Spawn site wraps it in a \`move ||\` closure so spawn_blocking owns
  the captured state. \`graph_handle.await\` keeps the same shape — a
  spawn_blocking JoinHandle is awaitable.

The blocking pool defaults to 512 threads, so reserving one slot for
graph_worker has no scheduling effect on download/clone/extract
spawn_blocking calls. Net effect: the resolve worker can no longer be
preempted by graph mutation bursts.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Optimal-hypothesis A/B from PR #2920's analysis: PR #2920's install
integration sets \`skip_preload=true\` on \`pipeline_deps_options\`, so
\`utoo install\` routes through channel \`mb_fetch_with_graph\` and
emits PackageResolved at full fetch rate. Bench data showed this
floods the download pipeline with concurrent tarball requests that
fight extract workers for blocking-pool slots, net p3_cold_install
regression of ~0.7s vs the legacy install path (5.95s) and Plan B's
inline+spawn_blocking variant (5.75s).

Drop \`skip_preload=true\` from \`pipeline_deps_options\`. \`utoo
install\` now routes through legacy preload+BFS, recovering the p3
win. \`utoo deps\` (lockfile-only) still hits channel
\`mb_fetch_with_graph\` via \`Self::build_deps\` which sets
\`skip_preload=true\` independently — keeps the p1 = 2.78s win.

Expected outcome:
- p1 (utoo deps): unchanged from PR #2920 ≈ 2.78s
- p3 (utoo install): reverts to legacy install ≈ 5.95s, vs PR #2920's 6.70s
- p0 (full cold): roughly Plan A's 7.95-8.79s

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
@elrrrrrrr elrrrrrrr added the benchmark Run pm-bench on PR label May 10, 2026
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Code Review

This pull request introduces significant performance optimizations to the manifest resolution and preloading pipeline, specifically targeting lockfile-only workloads. It adds standalone benchmarking tools, manifest-bench and preload-bench, to isolate and measure network and resolution overhead. Key improvements include a folded streaming graph build that integrates preloading with graph construction, switching JSON parsing to tokio::task::spawn_blocking to prevent runtime worker starvation, and increasing default fetch concurrency. Detailed instrumentation has been added to provide per-phase timing breakdowns. Review feedback highlights a bug in the success/fail metric tracking for fetches, a potential O(N) performance bottleneck in edge target processing, and an opportunity to eliminate redundant buffer clones during JSON parsing.

Comment on lines +467 to +475
// Empty result from a fetch is ambiguous (no transitives
// OR a fetch/parse failure). Track conservatively as
// success — the FETCH_TIMINGS-equivalent counter is
// omitted in this path on purpose to keep the future
// body lean.
stats.success += 1;
} else if out.fetched {
stats.success += 1;
}
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medium

The logic for tracking successful fetches is flawed. If a request fails (e.g., network error resulting in status == 0) or returns a non-200 status (e.g., 404), transitives will be empty and fetched will be true. The current code increments stats.success in both cases, leading to inaccurate performance metrics in the logs.

Suggested change
// Empty result from a fetch is ambiguous (no transitives
// OR a fetch/parse failure). Track conservatively as
// success — the FETCH_TIMINGS-equivalent counter is
// omitted in this path on purpose to keep the future
// body lean.
stats.success += 1;
} else if out.fetched {
stats.success += 1;
}
if out.fetched && out.status == 200 {
stats.success += 1;
} else if out.fetched {
stats.fail += 1;
}

Comment on lines +946 to +950
let primary_keys: Vec<(String, String)> = edge_targets
.keys()
.filter(|(n, _)| n == &msg.name)
.cloned()
.collect();
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medium

Iterating over all keys in edge_targets for every FetchEventMsg is an $O(N)$ operation where $N$ is the number of unique (name, spec) pairs currently being resolved. While likely acceptable for typical dependency trees, this could become a bottleneck for extremely large projects. Consider using a nested map structure (e.g., HashMap<String, Vec<String>>) to quickly retrieve all specs associated with a package name.

) -> Result<(FullManifest, Option<PrimarySettleResult>)> {
use simd_json::prelude::{ValueAsScalar, ValueObjectAccess};

let mut buf = (*raw).to_vec();
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medium

Cloning the entire manifest buffer into a Vec<u8> for simd_json is expensive on the hot path. Since simd_json requires a mutable buffer for in-place unescaping, and the raw bytes are stored in an immutable Arc<[u8]> within FullManifest, this copy is currently necessary. However, if performance remains a concern, exploring ways to pass ownership of the initial Vec<u8> from the network response directly to the parser before wrapping it in an Arc could eliminate this allocation.

elrrrrrrr and others added 2 commits May 10, 2026 21:53
The previous \`max(num_cpus, 8)\` rayon pool was tuned for resolve-path
manifest parse but the install-path's \`par_chunks(64)\` tarball extract
also rides the global rayon pool. Bench A/B on PR #2923 (channel resolve
+ legacy install) showed:

- mac run1 (clean CI): utoo p3 9.49s ±0.19, beats utoo-npm 12.64s
- mac run2 (busier CI): utoo p3 14.18s ±0.42, loses to utoo-npm 12.56s
  by 1.6s — utoo regressed +4.7s while utoo-npm only +-0.08s and
  bun +0.8s

linux 3 runs all show p3 1-3s gap vs utoo-next. Pattern: utoo
oversubscribes 8 rayon workers × par_chunks(64) = 512 in-flight disk
writes, which is fine on idle hardware but compounds under load.

Resolve-path doesn't actually need the bigger rayon pool: parse
already runs through \`tokio::task::spawn_blocking\` (512-slot pool)
in \`mb_resolve.rs\`, not rayon. The bigger rayon pool was solving
a problem in a path that was later swapped to a different mechanism.

Restore origin/next behavior: rayon at default \`num_cpus\` on Unix,
8MB stack on Windows for libdeflater. Expected outcome:

- p1: unchanged ≈ 2.66s (resolve uses tokio blocking pool, not rayon)
- p3: recovers to Plan A's ~5.95s on linux, ~9.5s on mac stably
- p0: improves vs prior PR #2923

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
PR #2916/#2920 switched manifest parse from \`rayon::spawn\` to
\`tokio::task::spawn_blocking\` on the theory that rayon's small pool
(num_cpus = 2 on GHA) added queue wait at 64× concurrent fetches.
That tradeoff worked for the channel mb_fetch_with_graph hot path
(\`utoo deps\`), but it routed the legacy preload+BFS install path's
manifest parse through tokio's blocking pool — the same pool used by
download / clone workers on \`utoo install\`. With 4647 deps × parse
× 2 hops, the contention with install IO workers added ~2s on
p3_cold_install on PR #2923 (channel resolve + legacy install).

Bench data on PR #2923 + rayon-pool revert (sha 39c8966):
- linux clean run: utoo p3 = 8.39s ±0.18 vs utoo-next p3 = 6.00s
  ±0.27 — utoo +2.39s gap with σ < 0.3 on both, ruling out CI noise
- utoo p1 = 2.79s avg (channel mb_fetch_with_graph still wins)

Restoring rayon::spawn keeps parse on its own pool (small but
isolated from install IO workers). Channel mb_fetch_with_graph in
mb_resolve.rs uses \`tokio::task::spawn_blocking\` directly for its
own combined parse so this revert doesn't affect the resolve hot
path's p1 numbers.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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📊 pm-bench-phases · 0445299 · linux (ubuntu-latest)

Workflow run — ant-design

PMs: utoo (this branch) · utoo-npm (latest published) · bun (latest)

npmjs.org

p0_full_cold

PM wall ±σ user sys RSS pgMinor
bun 9.19s 0.23s 10.36s 10.35s 769M 339.4K
utoo-next 8.25s 0.30s 10.69s 12.46s 989M 126.0K
utoo-npm 9.13s 1.04s 11.26s 12.89s 1.38G 184.2K
utoo 8.17s 0.29s 10.63s 12.23s 1007M 123.0K
PM vCtx iCtx netRX netTX cache node_mod lock
bun 13.7K 16.8K 1.20G 6M 1.89G 1.77G 1M
utoo-next 134.4K 97.2K 1.17G 5M 1.73G 1.73G 2M
utoo-npm 139.6K 105.3K 1.17G 5M 1.73G 1.73G 2M
utoo 127.9K 74.5K 1.17G 5M 1.73G 1.73G 2M

p1_resolve

PM wall ±σ user sys RSS pgMinor
bun 1.90s 0.04s 4.04s 1.03s 484M 163.0K
utoo-next 3.16s 0.05s 5.52s 1.97s 614M 88.5K
utoo-npm 3.11s 0.04s 5.56s 1.94s 607M 79.1K
utoo 2.66s 0.10s 5.37s 1.06s 1.12G 162.8K
PM vCtx iCtx netRX netTX cache node_mod lock
bun 7.8K 4.6K 204M 3M 108M - 1M
utoo-next 69.0K 115.3K 201M 2M 7M 3M 2M
utoo-npm 68.7K 113.7K 201M 2M 7M 3M 2M
utoo 38.8K 8.4K 201M 2M - 3M 3M

p3_cold_install

PM wall ±σ user sys RSS pgMinor
bun 6.59s 0.14s 6.39s 10.02s 615M 208.4K
utoo-next 6.05s 0.12s 4.94s 10.83s 479M 58.1K
utoo-npm 6.52s 0.17s 5.49s 11.21s 937M 107.5K
utoo 5.86s 0.25s 5.03s 10.69s 501M 67.0K
PM vCtx iCtx netRX netTX cache node_mod lock
bun 3.4K 6.7K 1.00G 3M 1.78G 1.78G 1M
utoo-next 90.0K 44.2K 999M 2M 1.72G 1.72G 2M
utoo-npm 100.5K 60.5K 999M 2M 1.72G 1.72G 2M
utoo 85.2K 44.5K 999M 2M 1.72G 1.72G 2M

p4_warm_link

PM wall ±σ user sys RSS pgMinor
bun 3.27s 0.08s 0.20s 2.39s 139M 33.1K
utoo-next 2.51s 0.38s 0.53s 3.86s 80M 18.1K
utoo-npm 2.46s 0.08s 0.55s 3.92s 85M 19.6K
utoo 2.41s 0.01s 0.52s 3.87s 81M 18.6K
PM vCtx iCtx netRX netTX cache node_mod lock
bun 299 24 5M 38K 1.93G 1.77G 1M
utoo-next 40.8K 18.1K 306K 12K 1.73G 1.73G 2M
utoo-npm 47.4K 21.5K 319K 26K 1.73G 1.73G 2M
utoo 43.9K 21.1K 306K 12K 1.73G 1.73G 2M

npmmirror.com

p0_full_cold

PM wall ±σ user sys RSS pgMinor
bun 33.22s 1.92s 9.67s 10.47s 534M 396.4K
utoo-next 28.63s 0.53s 7.41s 13.81s 510M 76.5K
utoo-npm 31.68s 1.68s 7.91s 14.94s 761M 132.7K
utoo 21.32s 0.48s 7.38s 13.63s 519M 85.8K
PM vCtx iCtx netRX netTX cache node_mod lock
bun 110.3K 3.4K 1.16G 13M 1.89G 1.77G 2M
utoo-next 233.4K 109.0K 1.01G 10M 1.73G 1.73G 2M
utoo-npm 242.0K 135.3K 1.02G 10M 1.73G 1.73G 2M
utoo 213.7K 119.5K 1.03G 10M 1.73G 1.73G 2M

p1_resolve

PM wall ±σ user sys RSS pgMinor
bun 3.82s 0.07s 3.75s 1.37s 510M 232.2K
utoo-next 5.40s 0.02s 1.59s 0.93s 87M 21.4K
utoo-npm 15.94s 17.47s 1.47s 1.02s 87M 21.2K
utoo 3.49s 0.19s 5.65s 1.13s 1.03G 140.2K
PM vCtx iCtx netRX netTX cache node_mod lock
bun 24.3K 2.5K 155M 4M 109M - 2M
utoo-next 45.7K 34.9K 16M 2M - 3M 2M
utoo-npm 46.9K 27.8K 16M 2M - 3M 2M
utoo 49.9K 6.3K 151M 3M - 3M 2M

p3_cold_install

PM wall ±σ user sys RSS pgMinor
bun 29.80s 8.15s 6.02s 9.29s 231M 89.9K
utoo-next 49.88s 27.68s 5.70s 12.05s 438M 58.3K
utoo-npm 40.12s 12.15s 6.23s 13.05s 616M 101.1K
utoo 28.11s 1.35s 5.71s 11.97s 447M 64.1K
PM vCtx iCtx netRX netTX cache node_mod lock
bun 74.6K 2.8K 1020M 10M 1.74G 1.74G 2M
utoo-next 172.1K 45.6K 1002M 7M 1.72G 1.72G 3M
utoo-npm 186.6K 81.3K 1001M 7M 1.72G 1.72G 3M
utoo 163.8K 50.2K 1002M 7M 1.72G 1.72G 3M

p4_warm_link

PM wall ±σ user sys RSS pgMinor
bun 3.35s 0.08s 0.19s 2.35s 138M 32.1K
utoo-next 2.37s 0.09s 0.52s 3.90s 81M 18.1K
utoo-npm 2.32s 0.05s 0.54s 3.95s 86M 19.4K
utoo 2.40s 0.16s 0.52s 3.92s 82M 18.9K
PM vCtx iCtx netRX netTX cache node_mod lock
bun 519 24 2M 60K 1.87G 1.77G 2M
utoo-next 41.8K 19.2K 337K 19K 1.73G 1.73G 3M
utoo-npm 49.0K 22.2K 338K 21K 1.73G 1.73G 3M
utoo 43.5K 20.1K 337K 20K 1.73G 1.73G 3M

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📊 pm-bench-phases · 0445299 · mac (macos-latest)

Workflow run — ant-design

PMs: utoo (this branch) · utoo-npm (latest published) · bun (latest)

npmjs.org

p0_full_cold

PM wall ±σ user sys RSS pgMinor
bun 18.99s 2.84s 7.01s 20.79s 783M 50.6K
utoo-npm 16.99s 2.07s 8.44s 18.88s 1.09G 107.3K
utoo 19.36s 3.59s 8.73s 21.07s 899M 60.6K
PM vCtx iCtx netRX netTX cache node_mod lock
bun 16.1K 145.7K - - 1.80G 1.94G 1M
utoo-npm 12.1K 344.3K - - 1.67G 1.91G 2M
utoo 13.7K 319.6K - - 1.67G 1.87G 2M

p1_resolve

PM wall ±σ user sys RSS pgMinor
bun 2.80s 0.18s 2.82s 1.35s 488M 31.7K
utoo-npm 4.14s 0.77s 4.17s 2.35s 582M 40.2K
utoo 3.49s 0.71s 4.24s 1.05s 606M 40.2K
PM vCtx iCtx netRX netTX cache node_mod lock
bun 33 25.6K - - 112M - 1M
utoo-npm 6 167.2K - - 27M 3M 2M
utoo 9 61.4K - - - 3M 3M

p3_cold_install

PM wall ±σ user sys RSS pgMinor
bun 13.92s 0.58s 3.58s 16.66s 532M 34.6K
utoo-npm 16.01s 0.46s 4.28s 20.35s 806M 82.3K
utoo 14.07s 1.09s 3.77s 17.81s 522M 36.5K
PM vCtx iCtx netRX netTX cache node_mod lock
bun 4.7K 134.6K - - 1.73G 1.97G 1M
utoo-npm 1.7K 233.8K - - 1.64G 1.88G 2M
utoo 1.5K 211.8K - - 1.64G 1.88G 2M

p4_warm_link

PM wall ±σ user sys RSS pgMinor
bun 6.16s 2.13s 0.12s 2.52s 53M 4.0K
utoo-npm 3.76s 0.32s 0.39s 2.47s 100M 7.4K
utoo 3.60s 0.14s 0.25s 2.37s 75M 5.9K
PM vCtx iCtx netRX netTX cache node_mod lock
bun 17.3K 751 - - 1.89G 1.94G 1M
utoo-npm 12.8K 67.5K - - 1.64G 1.87G 2M
utoo 14.0K 53.8K - - 1.64G 1.87G 2M

npmmirror.com

p0_full_cold

PM wall ±σ user sys RSS pgMinor
bun 35.47s 2.78s 6.29s 16.71s 559M 36.2K
utoo-npm 42.57s 1.19s 7.53s 22.20s 817M 79.9K
utoo 36.43s 6.18s 5.98s 16.85s 575M 37.9K
PM vCtx iCtx netRX netTX cache node_mod lock
bun 14.1K 184.9K - - 1.82G 1.93G 2M
utoo-npm 1.0K 480.3K - - 1.64G 1.90G 2M
utoo 1.1K 420.5K - - 1.64G 1.88G 2M

p1_resolve

PM wall ±σ user sys RSS pgMinor
bun 6.48s 1.34s 2.54s 1.37s 503M 32.8K
utoo-npm 3.74s 0.02s 1.25s 0.75s 97M 6.9K
utoo 3.28s 0.63s 4.08s 1.02s 579M 39.3K
PM vCtx iCtx netRX netTX cache node_mod lock
bun 32 29.1K - - 114M - 2M
utoo-npm 6 217.7K - - - 3M 2M
utoo 21 62.2K - - - 3M 3M

p3_cold_install

PM wall ±σ user sys RSS pgMinor
bun 24.59s 1.17s 4.06s 17.20s 250M 16.6K
utoo-npm 52.12s 4.43s 5.93s 20.21s 695M 79.4K
utoo 50.71s 5.49s 4.99s 18.25s 516M 35.5K
PM vCtx iCtx netRX netTX cache node_mod lock
bun 1.7K 151.3K - - 1.67G 1.94G 2M
utoo-npm 1.7K 366.2K - - 1.64G 1.91G 3M
utoo 2.3K 291.3K - - 1.64G 1.91G 3M

p4_warm_link

PM wall ±σ user sys RSS pgMinor
bun 4.82s 0.22s 0.11s 2.20s 47M 3.6K
utoo-npm 3.52s 0.10s 0.39s 2.72s 98M 7.3K
utoo 3.24s 0.29s 0.36s 2.58s 89M 6.7K
PM vCtx iCtx netRX netTX cache node_mod lock
bun 12.8K 866 - - 1.81G 1.94G 2M
utoo-npm 11.9K 69.3K - - 1.64G 1.91G 3M
utoo 12.8K 56.2K - - 1.64G 1.91G 3M

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