perf(wasm): sync init wasm in thread worker

[xusd320]

Fellow #2540
This pull request makes a minor update to how WebAssembly initialization is handled in the threadWorker.ts file. The change replaces the asynchronous initialization function with a synchronous one to better support worker thread spawning.

• Replaced the default import initWasm with the synchronous initialization function initSync from utoo, and updated the assignment of wasm_bindgen accordingly in threadWorker.ts.

[gemini-code-assist]

Summary of Changes

Hello @xusd320, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request focuses on optimizing WebAssembly integration within worker threads by transitioning from an asynchronous to a synchronous initialization method. This change aims to enhance the reliability and performance of worker thread spawning. Accompanying this core modification are various dependency updates to ensure compatibility and leverage the latest versions of underlying libraries.

Highlights

• WebAssembly Initialization: The WebAssembly initialization in threadWorker.ts has been switched from an asynchronous initWasm function to a synchronous initSync function to improve support for worker thread spawning.
• Dependency Updates: Several dependencies in Cargo.lock have been updated, including downgrades for windows-sys and socket2, and updates to specific git commits for tokio and wasm_thread related crates.

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[gemini-code-assist]

Code Review

This pull request updates the WebAssembly initialization in threadWorker.ts to use a synchronous function, initSync, which is crucial for supporting worker thread spawning as described. This change aligns with the stated goal of improving WASM performance in thread workers. The Cargo.lock file has been updated to reflect new dependency versions, including specific git references for tokio and wasm_thread forks, and some dependency downgrades.

[gemini-code-assist]

The stacker package now lists two different versions of windows-sys (0.52.0 and 0.59.0) as dependencies. This can lead to increased binary size and potential runtime conflicts due to multiple versions of the same crate being linked. It is best practice to consolidate to a single compatible version of a dependency across the project to avoid such issues. Please resolve this to use a single version of windows-sys for the stacker package.

 "windows-sys 0.59.0",

[github-actions]

📊 Performance Benchmark Report (with-antd)

🚀 Utoopack Performance Report: Async Task Scheduling Overhead Analysis

Report ID: utoopack_performance_report_20260127_091542
Generated: 2026-01-27 09:15:42
Trace File: trace_antd.json (1.5GB, 8.00M events)
Test Project: Unknown Project

---

📊 Executive Summary

This report analyzes the performance of Utoopack/Turbopack, covering the full spectrum of the Performance Analysis Protocol (P0-P4).

Key Findings

Metric	Value	Assessment
Total Wall Time	10,502.7 ms	Baseline
Total Thread Work	90,536.4 ms	~8.6x parallelism
Thread Utilization	78.4%	🆗 Average
turbo_tasks::function Invocations	3,881,441	Total count
Meaningful Tasks (≥ 10µs)	1,545,434	(39.8% of total)
Tracing Noise (< 10µs)	2,336,007	(60.2% of total)

Workload Distribution by Tier

Category	Tasks	Total Time (ms)	% of Work
P0: Runtime/Resolution	1,061,284	54,827.0	60.6%
P1: I/O & Heavy Tasks	38,071	3,714.1	4.1%
P3: Asset Pipeline	28,198	4,573.3	5.1%
P4: Bridge/Interop	0	0.0	0.0%
Other	417,881	20,127.2	22.2%

---

⚡ Parallelization Analysis (P0-P2)

Thread Utilization

Metric	Value
Number of Threads	11
Total Thread Work	90,536.4 ms
Avg Work per Thread	8,230.6 ms
Theoretical Parallelism	8.62x
Thread Utilization	78.4%

Assessment: With 11 threads available, achieving 8.6x parallelism indicates reasonable throughput.

---

📈 Top 20 Tasks (Global)

These are the most significant tasks by total duration:

Total (ms)	Count	Avg (µs)	% Work	Task Name
45,718.2	879,618	52.0	50.5%	turbo_tasks::function
8,730.2	124,002	70.4	9.6%	task execution completed
6,470.6	83,912	77.1	7.1%	turbo_tasks::resolve_call
3,073.1	33,126	92.8	3.4%	analyze ecmascript module
2,183.3	67,043	32.6	2.4%	precompute code generation
2,102.9	68,281	30.8	2.3%	resolving
1,800.7	36,045	50.0	2.0%	module
1,757.0	21,111	83.2	1.9%	effects processing
1,533.4	11,632	131.8	1.7%	process parse result
1,214.0	6,641	182.8	1.3%	parse ecmascript
1,102.4	33,305	33.1	1.2%	process module
1,039.3	36,120	28.8	1.1%	internal resolving
846.7	29,109	29.1	0.9%	resolve_relative_request
687.7	1,924	357.4	0.8%	analyze variable values
501.1	21,353	23.5	0.6%	handle_after_resolve_plugins
468.1	10,878	43.0	0.5%	code generation
467.7	1,947	240.2	0.5%	swc_parse
466.5	16,024	29.1	0.5%	resolve_module_request
386.1	17,732	21.8	0.4%	resolved
348.4	4,256	81.9	0.4%	read file

---

🔍 Deep Dive by Tier

🔴 Tier 1: Runtime & Resolution (P0)

Focus: Task scheduling and dependency resolution.

Metric	Value	Status
Total Scheduling Time	54,827.0 ms	⚠️ High
Resolution Hotspots	9 tasks	🔍 Check Top Tasks

Potential P0 Issues:

• Low thread utilization (78.4%) suggests critical path serialization or lock contention.
• 2,336,007 tasks < 10µs (60.2%) contribute to scheduler pressure.

🟠 Tier 2: Physical & Resource Barriers (P1)

Focus: Hardware utilization, I/O, and heavy monoliths.

Metric	Value	Status
I/O Work (Estimated)	3,714.1 ms	✅ Healthy
Large Tasks (> 100ms)	16	🚨 Critical

Potential P1 Issues:

• 16 tasks exceed 100ms. These "Heavy Monoliths" are prime candidates for splitting.

🟡 Tier 3: Architecture & Asset Pipeline (P2-P3)

Focus: Global state and transformation pipeline.

Metric	Value	Status
Asset Processing (P3)	4,573.3 ms	5.1% of work
Bridge Overhead (P4)	0.0 ms	✅ Low

---

💡 Recommendations (Prioritized P0-P2)

🚨 Critical: (P0) Improvement

Problem: 78.4% thread utilization.
Action:

1. Profile lock contention if utilization < 60%.
2. Convert sequential await chains to try_join.

⚠️ High Priority: (P1) Optimization

Problem: 16 heavy tasks detected.
Action:

1. Identify module-level bottlenecks (e.g., barrel files).
2. Optimize I/O batching for metadata.

⚠️ Medium Priority: (P3) Pipeline Efficiency

Action:

1. Review transformation logic for frequently changed assets.
2. Minimize cross-language serialization (P4) if overhead exceeds 10%.

---

📐 Diagnostic Signal Summary

Signal	Status	Finding
Tracing Noise (P0)	⚠️ Significant	60.2% of tasks < 10µs
Thread Utilization (P0)	✅ Good	78.4% utilization
Heavy Monoliths (P1)	⚠️ Detected	16 tasks > 100ms
Asset Pipeline (P3)	🔍 Review	4,573.3 ms total
Bridge/Interop (P4)	✅ Low	0.0 ms total

---

🎯 Action Items (Comprehensive P0-P4)

1. [P0] Investigate task scheduling gaps for incremental gains
2. [P1] Breakdown heavy monolith tasks (>100ms) to improve granularity
3. [P1] Review I/O patterns for potential batching opportunities
4. [P3] Optimize asset transformation pipeline hot-spots
5. [P4] Reduce "chatty" bridge operations if interop overhead is significant

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Report generated by Utoopack Performance Analysis Agent on 2026-01-27
Following: Utoopack Performance Analysis Agent Protocol