I made a build visualizer to understand Bun's compile times
summary
The author created buildprof, an open-source tracing tool, to diagnose why Bun's Rust build was significantly faster than its previous Zig build. By visualizing the build as a process tree on a timeline, the author discovered that the Zig build's slowness was primarily caused by Full Link-Time Optimization (LTO) and a monolithic module structure. This demonstrates that build performance issues are often structural or configuration-based rather than inherent to the language itself.
key points
- buildprof captures the entire process tree of a build, making it agnostic to the specific build system used and capable of tracking custom scripts and file dependencies.
- Analysis revealed that Bun's Zig build was slowed down by Full LTO in both Bun's code and its bundled WebKit libraries, whereas the Rust build used ThinLTO.
- A fundamental structural difference was found where Rust's division into over 90 crates allowed for much better parallelism than Zig's single-module approach.
who should read it
Software engineers and DevOps professionals who struggle with slow compilation times and need a way to identify specific bottlenecks in their build pipelines.
discussion positive
consensus
Commenters agree that Zig's current compilation bottlenecks stem from its single-unit compilation model and lack of parallel semantic analysis, which contrasts with Rust's crate-based parallelism. While splitting Zig modules could potentially speed up builds, it would currently require sacrificing language features like generics and slices. There is general agreement that Zig excels in debug and incremental build speeds compared to Rust, despite slower full release builds.
top insight
The lack of parallelism in Zig's semantic analysis is a deliberate trade-off to maintain build determinism, as previous attempts at multi-threading resulted in non-deterministic builds. This explains why Zig cannot simply 'turn on' parallelism to match Rust's build speeds without significant architectural work on the compiler's Sema.zig. This insight provides the critical technical reason for the performance gap observed in the analysis.
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