官方评估数据显示，在处理真实复杂的 AI 任务时，该技术将离线处理吞吐量最高提升 1.87 倍，在线服务吞吐量平均提升 1.96 倍。
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Randomly selecting border points or using simple geometric divisions (squares/hexagons) results in too many border points per cluster (50-80). This leads to a shortcut explosion (N*(N-1)/2 shortcuts), making the files large and and calculations slow.，这一点在heLLoword翻译官方下载中也有详细论述
The performance characteristics are attractive with incredibly fast cold starts and minimal memory overhead. But the practical limitation is language support. You cannot run arbitrary Python scripts in WASM today without compiling the Python interpreter itself to WASM along with all its C extensions. For sandboxing arbitrary code in arbitrary languages, WASM is not yet viable. For sandboxing code you control the toolchain for, it is excellent. I am, however, quite curious if there is a future for WASM in general-purpose sandboxing. Browsers have spent decades solving a similar problem of executing untrusted code safely, and porting those architectural learnings to backend infrastructure feels like a natural evolution.