社内勉強会資料_Two Papers Contribute to Faster Python.pdf
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The document discusses two advancements aimed at increasing Python's performance: multi-level quickening, which optimizes the CPython interpreter through type feedback and specialized bytecodes, and copy-and-patch JIT compilation for faster execution. Python 3.10 and later versions show significant speed improvements, with Python 3.13 introducing a basic JIT compiler. It emphasizes the importance of upgrading to enhance efficiency and reduce resource consumption.
社内勉強会資料_Two Papers Contribute to Faster Python.pdf
- 1. Two Papers Contribute to Faster Python
- 2. Table of Contents Faster CPython Project Specializing Adaptive Interpreter Copy-and-patch JIT Compilation
- 4. x5 Speed Python 3.10 Python 3.11 Python 3.12 Python 3.13 Summarized in Implementation plan for speeding up CPython ⬆50 % ⬆50 % ⬆50 % ⬆50 % Table of contents
- 5. Specialized Adaptive Interpreter Motivated by Multi-level Quickening: The Key to Interpreter Performance
- 6. Multi-level Quickening: The Key to Interpreter Performance Background Interpreters for dynamically-typed programming languages are slow. CPython Interpreter Python Source Code Python Virtual Machine Bytecode
- 7. Multi-level Quickening: The Key to Interpreter Performance First-level Quickening: Type Feedback
- 8. Multi-level Quickening: The Key to Interpreter Performance Second-level Quickening: Type Propagation
- 9. Multi-level Quickening: The Key to Interpreter Performance Optimized Instruction Derivatives i.e. Make instructions more optimized for machine data types ● Mapping Integer Numbers ○ uint64_t ? int64_t ? int32_t ● Mapping Floating Point Number ● Mapping Complex Numbers.
- 10. Multi-level Quickening: The Key to Interpreter Performance Super-instructions: concatenates frequently occurring sequences of interpreter instructions >>> dis.dis(add_two) 1 0 RESUME 0 2 LOAD_FAST 0 (a) 4 LOAD_FAST 1 (b) 6 BINARY_OP 0 (+) 10 RETURN_VALUE >>> dis.dis(add_two, adaptive=True) 1 0 RESUME 0 2 LOAD_FAST__LOAD_FAST 0 (a) 4 LOAD_FAST 1 (b) 6 BINARY_OP_ADD_FLOAT 0 (+) 10 RETURN_VALUE >>> def add_two(a, b): return a + b
- 11. Multi-level Quickening: The Key to Interpreter Performance Performance Results
- 12. Quickening & Specialization in Reality Python 3.11 ● Specialization clicks in after 8 executions. ● 25% faster than Python 3.10. Python 3.12 ● Specialization clicks in after 2 executions. ● Special more new bytecodes. Table of contents
- 13. Copy-and-patch JIT Compilation Motivated by Copy-and-Patch Compilation: A fast compilation algorithm for high-level languages and bytecode
- 14. Copy-and-Patch Compilation: A fast compilation algorithm for high-level languages and bytecode What’s JIT Compilation ● Just in time Compilation, only compile on demand when running for the 1st time. ● In contrast, compiled languages is using “Ahead of time”, compile before being used.
- 15. Copy-and-Patch Compilation: A fast compilation algorithm for high-level languages and bytecode Interpreting Parse into Bytecode Execution Copy-and-Patch JIT Compilation Copy Bytecode Execution Patch arguments Running a function several times
- 16. Copy-and-Patch Compilation: A fast compilation algorithm for high-level languages and bytecode Normal Interpreting Each time we run a function, CPython parse it into bytecodes, in a loop: >>> def get_one(): ... a = 1 ... return a >>> get_one() >>> get_one() 1 0 RESUME 0 2 2 LOAD_CONST 1 (1) 4 STORE_FAST 0 (a) 3 6 LOAD_FAST 0 (a) 8 RETURN_VALUE 1 0 RESUME 0 2 2 LOAD_CONST 1 (1) 4 STORE_FAST 0 (a) 3 6 LOAD_FAST 0 (a) 8 RETURN_VALUE
- 17. Copy-and-Patch Compilation: A fast compilation algorithm for high-level languages and bytecode Copy-and-Patch JIT >>> def get_one(): ... a = 1 ... return a A function with the same functionality, but written in a lower language, e.g. C or Assembly. Table of contents Caveat Copy Instruction is kind of code generation, may expose security concerns. iOS prohibits such dynamic code generation.
- 18. Copy-and-Patch Compilation in Reality Table of contents A basic JIT compiler will be added in Python 3.13 (disabled in beta at the moment)
- 19. Take Away ● Upgrade to the latest Python version (official releases) ○ Save energy ○ Save money ○ Save environment
- 20. References ● Implementation plan for speeding up CPython ● Multi-Level Quickening: Ten Years Later ● Copy-and-Patch Compilation: A fast compilation algorithm for high-level languages and bytecode ● Python 3.13 gets a JIT