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Applying a Tracing JIT to an Interpreter | PyPy
https://www.pypy.org/posts/2009/03/applying-tracing-jit-to-interpreter-3287844903778799266.html
JIT help — PyPy documentation
https://doc.pypy.org/en/latest/jit_help.html
<pypy>--jit [options] where options is a comma-separated list of OPTION=VALUE: decay=N amount to regularly decay counters by (0=none, 1000=max) (default 40) disable_unrolling=N ... trace_eagerness=N number of times a guard has to fail before we start compiling a …
Better JIT Support for Auto-Generated Python Code | PyPy
https://www.pypy.org/posts/2021/09/jit-auto-generated-code.html
PyPy's Approach to Implementing Dynamic Languages Using a Tracing JIT …
https://www.microsoft.com/en-us/research/video/pypys-approach-to-implementing-dynamic-languages-using-a-tracing-jit-compiler/
In the second part of the talk I will give an introduction into the PyPy project and its approach to virtual machine construction. PyPy is an environment to implement dynamic languages way using a modular tracing JIT. It hopes to overcome the difficulties and make implementing fast dynamic languages significantly easier.
JIT hooks — PyPy documentation
https://doc.pypy.org/en/latest/jit-hooks.html
JIT hooks¶. There are several hooks in the pypyjit module that may help you with understanding what pypy’s JIT is doing while running your program:. set_compile_hook (callable, operations=True) ¶. Set a compiling hook that will be called each time a loop is compiled. The callable will be called with the pypyjit.JitLoopInfo object. Refer to it’s documentation for details.
python - What kind of JIT compiler is used by PyPy?
https://stackoverflow.com/questions/37377787/what-kind-of-jit-compiler-is-used-by-pypy
Show activity on this post. As stated in Roland Smith's answer, PyPy uses a form of tracing JIT compiler. A tracing JIT compiles only the "used parts" by definition. Mind you, this doesn't make it any less real than some hypothetical JIT that starts off by compiling the whole program during startup.
Tutorial Part 2: Adding a JIT | PyPy
https://www.pypy.org/posts/2011/04/tutorial-part-2-adding-jit-8121732841568309472.html
A bit about Tracing JIT Compilers. It's worth it at this point to read up on how tracing JIT compilers work. Here's a brief explanation: The interpreter is usually running your interpreter code as written. When it detects a loop of code in the target language (BF) is executed often, that loop is considered "hot" and marked to be traced.
PyPy Status Blog: Applying a Tracing JIT to an Interpreter
https://morepypy.blogspot.com/2009/03/applying-tracing-jit-to-interpreter.html
The tracing JIT will at one point trace the execution of the while loop in sum_1_to_n. The trace might look as follows: guard_true (n >= 0); result += n; n -= 1; <loop_back>. This trace will then be turned into machine code. Note that the machine code loop is by itself infinite and can only be left via a guard failure.
Tracing the Meta-Level: PyPy’s Tracing JIT Compiler
https://www3.hhu.de/stups/downloads/pdf/BoCuFiRi09_246.pdf
ing JIT compiler. Contrary to the tracing JITs for dynamic languages that currently exist, PyPy’s tracing JIT operates \one level down", i.e., it traces the execution of the inter-preter, as opposed to the execution of the user program. The fact that the program the tracing JIT compiles is in our case always an interpreter brings its own set ...
Tracing the meta-level: PyPy's tracing JIT compiler
https://dl.acm.org/doi/10.1145/1565824.1565827
Tracing identifies frequently executed code (hot spots), highlighting the program parts that would benefit most from JIT compilation. The PyPy project is a Python-based framework for implementing language interpreters. Embedding tracing JIT compilation techniques in the framework makes it possible to apply those techniques to the interpreter.
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