chore(pack): sync latest turbopack canary

[fireairforce]

Summary

• Update the next.js submodule to utooland/next.js@9c274924f2, based on the current vercel/next.js@7421a868ad canary tip.
• Preserve the Utoo WASM/browser-worker adaptations while resolving the latest TurboTasks and Turbopack APIs, then refresh the generated @utoo/web binding declarations.
• Wire the new Pack module and resolver options: production export-name mangling, compact production CSS Module identifiers with readable development identifiers, and project-root resolution for server-relative requests.
• Regenerate snapshots for the new 13-character base38 output hashes and add focused regressions for development CSS Module names and root-relative client/server imports.

Performance impact

• Production ESM exports can now use shorter mangled names.
• Production CSS Module identifiers no longer retain debug path prefixes, while development output stays readable.
• The synced canary includes the latest Turbo persistence key-ordering and SST lookup optimization.

Verification

• cargo fmt
• cargo clippy --all-targets -- -D warnings --no-deps
• cargo test -p pack-tests — 135 passed
• npm run build:local --workspace @utoo/pack
• npm test --workspace shared-runtime-async-module
• npm run build:local --workspace @utoo/web
• npx biome ci .
• npx tombi format --check
• typos
• Submodule full clippy, turbo-persistence, turbo-rcstr, AssetIdent, native/WASI/browser-WASM targeted checks

[chatgpt-codex-connector]

Codex Review Summary

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Review	Status	Commit	Review trigger
📝 Code Review	✅ Completed 2026-08-29T12:33:33.307023Z	f354f16	PR opened

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[chatgpt-codex-connector]

💡 Codex Review

Here are some automated review suggestions for this pull request.

Reviewed commit: f354f163cc

ℹ️ About Codex in GitHub

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• Open a pull request for review
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If Codex has suggestions, it will comment; otherwise it will react with 👍.

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[github-actions]

📊 Performance Benchmark Report (with-antd)

Utoopack Performance Report

Report ID: utoopack_performance_report_20260829_130800
Generated: 2026-08-29 13:08:00
Trace File: trace_antd.json (0.3GB, 0.82M spans)
Test Project: examples/with-antd

---

Executive Summary

Metric	Value	Assessment
Total Wall Time	6,225.8 ms	Baseline
Total Thread Work (de-duped)	19,178.9 ms	Non-overlapping busy time
Effective Parallelism	3.1x	thread_work / wall_time
Working Threads	10	Threads with actual spans
Thread Utilization	30.8%	⚠️ Suboptimal
Total Spans	819,244	All B/E + X events
Meaningful Spans (>= 10us)	220,416	(26.9% of total)
Tracing Noise (< 10us)	598,828	(73.1% of total)

---

Build Phase Timeline

Shows when each build phase is active and how much CPU it consumes.
Self-Time is the time spent exclusively in that phase (excluding children).

Phase	Spans	Inclusive (ms)	Self-Time (ms)	Wall Range (ms)
Resolve	50,274	7,121.2	1,921.9	3,197.4
Parse	8,172	1,342.2	1,007.4	5,704.3
Analyze	140,726	39,519.2	9,048.0	5,618.7
Chunk	5,767	5,509.1	917.5	2,210.6
Codegen	12,422	2,282.6	1,435.5	1,913.1
Emit	32	34.6	17.3	8.0
Other	3,023	5,904.7	3,257.1	6,225.8

---

Workload Distribution by Diagnostic Tier

Category	Spans	Inclusive (ms)	% Work	Self-Time (ms)	% Self
P0: Scheduling & Resolution	191,382	47,149.2	245.8%	11,161.2	58.2%
P1: I/O & Heavy Tasks	2,903	96.3	0.5%	79.0	0.4%
P2: Architecture (Locks/Memory)	0	0.0	0.0%	0.0	0.0%
P3: Asset Pipeline	25,003	9,174.6	47.8%	3,382.7	17.6%
P4: Bridge/Interop	0	0.0	0.0%	0.0	0.0%
Other	1,128	5,293.5	27.6%	2,981.8	15.5%

---

Top 20 Tasks by Self-Time

Self-time is the exclusive duration: time spent in the task itself, not in sub-tasks.
This is the most accurate indicator of where CPU cycles are actually spent.

Self (ms)	Inclusive (ms)	Count	Avg Self (us)	P95 Self (ms)	Max Self (ms)	% Work	Task Name	Top Caller
4,662.5	25,010.0	97,218	48.0	0.1	16.4	24.3%	module	module (62%)
2,184.4	2,341.3	2,456	889.4	2.9	228.4	11.4%	analyze ecmascript module	module (73%)
1,971.0	2,039.7	20	98550.7	297.6	446.4	10.3%	save snapshot	persist (5%)
1,356.6	11,056.8	31,131	43.6	0.1	5.7	7.1%	process module	process module (81%)
1,272.1	3,517.8	27,371	46.5	0.1	7.7	6.6%	internal resolving	internal resolving (77%)
954.3	1,289.1	6,003	159.0	0.6	44.8	5.0%	parse ecmascript	parse ecmascript (65%)
816.6	893.5	10,129	80.6	0.3	9.1	4.3%	precompute code generation	generate merged code (38%)
797.8	5,235.8	3,982	200.3	0.3	86.9	4.2%	chunking	chunking (44%)
711.5	857.7	7,210	98.7	0.4	90.7	3.7%	compute async module info	compute async module info (57%)
641.1	3,594.7	22,201	28.9	0.0	5.4	3.3%	resolving	module (55%)
585.5	1,950.2	861	680.1	1.8	223.7	3.1%	generate merged code	chunking (48%)
401.3	401.3	329	1219.7	0.9	240.3	2.1%	generate source map	code generation (83%)
328.9	710.5	130	2529.9	4.6	188.2	1.7%	emit code	generate merged code (42%)
249.5	474.0	1,561	159.8	0.1	123.2	1.3%	write all entrypoints to disk	write all entrypoints to disk (16%)
217.6	987.8	1,964	110.8	0.2	41.1	1.1%	code generation	code generation (81%)
116.6	269.5	1,736	67.2	0.1	9.3	0.6%	compute async chunks	compute async chunks (44%)
75.3	93.7	811	92.9	0.0	25.2	0.4%	compute binding usage info	compute binding usage info (47%)
71.0	71.0	7	10142.2	38.2	44.1	0.4%	blocking	save snapshot (43%)
53.1	53.1	2,166	24.5	0.0	0.4	0.3%	read file	parse ecmascript (91%)
44.7	79.1	1,873	23.9	0.0	16.0	0.2%	collect mergeable modules	collect mergeable modules (100%)

---

Critical Path Analysis

The longest sequential dependency chains that determine wall-clock time.
Focus on reducing the depth of these chains to improve parallelism.

Rank	Self-Time (ms)	Depth	Path
1	490.5	3	persist → save snapshot → blocking
2	412.9	6	chunking → generate merged code → emit code → emit code → emit code → read file
3	274.2	4	chunking → generate merged code → emit code → generate source map
4	228.5	3	process module → process module → analyze ecmascript module
5	154.5	2	save snapshot → blocking

---

Batching Candidates

High-volume tasks dominated by a single parent. If the parent can batch them,
it drastically reduces scheduler overhead.

Task Name	Count	Top Caller (Attribution)	Avg Self	P95 Self	Total Self
process module	31,131	process module (81%)	43.6 us	0.07 ms	1,356.6 ms
internal resolving	27,371	internal resolving (77%)	46.5 us	0.09 ms	1,272.1 ms

---

Duration Distribution

Range	Count	Percentage
<10us	598,828	73.1%
10us-100us	145,136	17.7%
100us-1ms	64,313	7.9%
1ms-10ms	10,746	1.3%
10ms-100ms	194	0.0%
>100ms	27	0.0%

---

Action Items

1. [P0] Focus on tasks with the highest Self-Time — these are where CPU cycles are actually spent.
2. [P0] Use Batching Candidates to identify callers that should use try_join or reduce #[turbo_tasks::function] granularity.
3. [P1] Check Build Phase Timeline for phases with disproportionate wall range vs. self-time (= serialization).
4. [P1] Inspect P95 Self (ms) for heavy monolith tasks. Focus on long-tail outliers, not averages.
5. [P1] Review Critical Paths — reducing the longest chain depth directly improves wall-clock time.
6. [P2] If Thread Utilization < 60%, investigate scheduling gaps (lock contention or deep dependency chains).

Report generated by Utoopack Performance Analysis Agent