On Sun, 28 Jan 2018, Etienne Robillard wrote:
Is it possible to use the PyPy JIT compiler embedded into a CPython
(Django) application?
I would like to translate a Django app into C code then compile the
binary with clang to optimize the code with a JIT engine.
What do you think?
I think that you might be confused about the fundamentals of the
technologies involved here.
Once you translate a Django app into C code (let's assume this is actually
possible for the sake of the argument) and then compile it into machine
code using clang there is nothing more left for a JIT to operate upon,
because machine code is interpreted directly by the CPU.
Tracing JIT engines like PyPy translate bytecode into machine code on the
fly taking into account invariants discovered during runtime, which
theoretically enables them to outperform machine code generated without
knowing the data it processes, and, in any case, run a lot faster than the
interpreted byte code.
A possible source of confusion is that people often speak of speeding
things up with LLVM (or nowadays even GCC) JIT; in most cases this amounts
to so called method level JITs where specific isolated functions are
compiled on the fly into machine code by the corresponding JIT backend and
then called from the bytecode interpreter instead of actually interpreting
the original bytecode for the method.
Anyways, having that said, I can't even infer what your original line of
thinking was to embed what into what to speed up what exactly...
--
Sincerely yours,
Yury V. Zaytsev
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