With that, I built a gigaprompt to ensure Opus 4.5 accounted for both the original Python implementation and a few new ideas I had, such as supersampling to antialias the output.
In reality, the effect of JIT compilation is broader - execution can slow down for up to ~1ms even for sljit, because of other related things, mostly cold processor cache and effects of increased memory pressure (rapid allocations / deallocations related to code generation and JIT compilation). Therefore, on systems executing a lot of queries per second, it's recommended to avoid JIT compilation for very fast queries such as point lookups or queries processing only a few records. By default, jit_above_cost parameter is set to a very high number (100'000). This makes sense for LLVM, but doesn't make sense for faster providers.
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简化流程： 通过直接在 Gradle 中配置源目录和输出目录，整个开发流程变得更加简单和集成。
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