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  1. Apr 11, 2024 · Add GPU support. The JIT is currently CPU-only. It does not, for example, offload NumPy array computations to CUDA GPUs, as JITs like Numba do. There is already a rich ecosystem of tools for accelerating these sorts of specialized tasks, and CPython’s JIT is not intended to replace them.

  2. Oct 23, 2012 · To answer the question you meant to ask: CPython, 3.x or otherwise, does not, never did, and likely never will, contain a JIT compiler. Some other Python implementations (PyPy natively, Jython and IronPython by re-using JIT compilers for the virtual machines they build on) do have a JIT compiler.

  3. JIT works well when you take a very small language (s.a. bytecode) which leaves you a lot of wiggle room for implementation (eg. memory manipulation, modifying large portions of the program w/o affecting programmer's editing workflow).

  4. A large reason CPython doesn't have a JIT is the extra complexity it introduces to the core implementation and issues regarding C extensions. Pypy is a very impressive piece of software but it has some issues with libraries which rely on C extensions which is a deal breaker for some.

  5. Apr 12, 2024 · PEP 744 is an informational PEP answering many common questions about CPython 3.13’s new experimental JIT compiler. My main goal for this PEP is to build community consensus around the specific criteria that the JIT should meet in order to become a permanent, non-experimental part of CPython.

  6. Sep 19, 2022 · There is no built-in JIT (Just in Time Compiling) for CPython (meaning it does not compile the code to machine instructions for a specific CPU). On the other hand, there is PyPy which is...

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  8. Jun 18, 2024 · Because the CPython JIT uses LLVM, "we have incredible platform support right out of the box". It runs on all of the most popular operating systems (Linux, macOS, and Windows) for x86_64, as well as 32-bit Windows on x86; it also supports the three OSes on Arm 64-bit processors.

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