The Cost of Speed: JIT's Initial Warmup #jit

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Clearly explains the critical tradeoff (initial slowness for massive later gain) using the compelling PyPy speed statistics as evidence.

This is what's known as warmup time and it's a fascinating tradeoff because it means a jit-powered program is actually slower at the very beginning than a program that's just being interpreted. It has to pay that upfront cost of profiling before it can cash in, but once those hotspots are compiled, the long Run performance can be unbelievably better. A perfect example of this is Pi Pi. It's a version of Python that uses a JIT compiler for programs that run for a while. It is, on average, a whopping 4.4 times faster than the standard Python interpreter. That's a massive speed boost, but here's the price you pay during that initial warm-up. While it's still trying to figure out what to compile. PIE Pi can actually be about five times slower than the standard version. It's a classic case of short-term pain for long-term gain.

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