Not So Fast: Analyzing the Performance of WebAssembly vs. Native Code
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Abstract (arXiv)
All major web browsers now support WebAssembly, a low-level bytecode intended to serve as a compilation target for code written in languages like C and C++. A key goal of WebAssembly is performance parity with native code; previous work reports near parity, with many applications compiled to WebAssembly running on average 10% slower than native code. However, this evaluation was limited to a suite of scientific kernels, each consisting of roughly 100 lines of code. Running more substantial applications was not possible because compiling code to WebAssembly is only part of the puzzle: standard Unix APIs are not available in the web browser environment. To address this challenge, we build Browsix-Wasm, a significant extension to Browsix that, for the first time, makes it possible to run unmodified WebAssembly-compiled Unix applications directly inside the browser. We then use Browsix-Wasm to conduct the first large-scale evaluation of the performance of WebAssembly vs. native. Across the SPEC CPU suite of benchmarks, we find a substantial performance gap: applications compiled to WebAssembly run slower by an average of 45% (Firefox) to 55% (Chrome), with peak slowdowns of 2.08x (Firefox) and 2.5x (Chrome). We identify the causes of this performance degradation, some of which are due to missing optimizations and code generation issues, while others are inherent to the WebAssembly platform.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Jan 2019.
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Citing papers per year: 2024: 2.
2 papers.
- 2024Anatomizing Deep Learning Inference in Web Browserscited by 6
- 2024Multi-modal Learning for WebAssembly Reverse Engineeringcited by 0
- 2024Multi-modal Learning for WebAssembly Reverse Engineering4 Apr 2024
- 2024Anatomizing Deep Learning Inference in Web Browsers8 Feb 2024