diff --git a/_posts/2020-06-29-release-the-gil-pt.-2.md b/_posts/2020-06-29-release-the-gil-pt.-2.md index bb4eaf2..2764c60 100644 --- a/_posts/2020-06-29-release-the-gil-pt.-2.md +++ b/_posts/2020-06-29-release-the-gil-pt.-2.md @@ -3,7 +3,7 @@ layout: post title: "Release the GIL: Part 2 - Pybind11, PyO3" description: "More Python Parallelism" category: -tags: [python] +tags: [python, rust, c++] --- I've been continuing experiments with parallelism in Python; while these techniques are a bit niche, @@ -26,6 +26,9 @@ and Python", and they certainly deliver on that. Setting up a hybrid project whe and Python (using setuptools) could coexist was straight-forward, and the repository also works as [a template](https://github.com/speice-io/release-the-gil-pybind11/settings) for future projects. +TODO: Include anything about how Pybind11 and Cython are similar because of compilation to C++? +Maybe also talk about project setup being a good deal more complicated? + Just like the previous post, we'll examine a simple Fibonacci sequence implementation to demonstrate how Python's threading model interacts with Pybind11: @@ -68,10 +71,28 @@ std::uint64_t fibonacci_nogil(std::uint64_t n) { py::gil_scoped_release release; return fibonacci(n); } + +PYBIND11_MODULE(speiceio_pybind11, m) { + + m.def("fibonacci_gil", &fibonacci_gil, R"pbdoc( + Calculate the Nth Fibonacci number while implicitly holding the GIL + )pbdoc"); + + m.def("fibonacci_nogil", &fibonacci_nogil, + R"pbdoc( + Calculate the Nth Fibonacci number after explicitly unlocking the GIL + )pbdoc"); + +#ifdef VERSION_INFO + m.attr("__version__") = VERSION_INFO; +#else + m.attr("__version__") = "dev"; +#endif +} ``` -Admittedly, the project setup is significantly more involved than Cython or Numba. I've omitted -those steps here, but the full project is available at [INSERT LINK HERE]. +After the code is installed into a `virtualenv` or similar setup, we can use the functions to +demonstrate GIL unlocking: ```python # The billionth Fibonacci number overflows `std::uint64_t`, but that's OK; @@ -161,3 +182,120 @@ t1.join(); t2.join() Finally, it's import to note that scheduling matters; in this example, threads run in serial because the GIL-locked thread is started first. + +TODO: Note about double-unlocking: + +```c++ +void recurse_unlock() { + py::gil_scoped_release release; + return recurse_unlock(); +} +``` + +>
+> Python 3.8.2 (default, Apr 27 2020, 15:53:34) +> [GCC 9.3.0] on linux +> Type "help", "copyright", "credits" or "license" for more information. +> >>> from speiceio_pybind11 import recurse_unlock +> >>> recurse_unlock() +> Fatal Python error: PyEval_SaveThread: NULL tstate +> Python runtime state: initialized +> +> Current thread 0x00007f213a627740 (most recent call first): +> File "+ +# PyO3 + +```python +N = 1_000_000_000; + +from speiceio_pyo3 import fibonacci_gil, fibonacci_nogil +``` + +```python +%%time +_ = fibonacci_gil(N) +``` + +>", line 1 in +> [1] 34943 abort (core dumped) python +>
+> CPU times: user 283 ms, sys: 0 ns, total: 283 ms +> Wall time: 282 ms +>+ +```python +%%time +_ = fibonacci_nogil(N) +``` + +>
+> CPU times: user 284 ms, sys: 0 ns, total: 284 ms +> Wall time: 284 ms +>+ +```python +%%time +from threading import Thread + +# Create the two threads to run on +t1 = Thread(target=fibonacci_gil, args=[N]) +t2 = Thread(target=fibonacci_gil, args=[N]) +# Start the threads +t1.start(); t2.start() +# Wait for the threads to finish +t1.join(); t2.join() +``` + +>
+> CPU times: user 503 ms, sys: 3.83 ms, total: 507 ms +> Wall time: 506 ms +>+ +```python +%%time + +t1 = Thread(target=fibonacci_nogil, args=[N]) +t2 = Thread(target=fibonacci_gil, args=[N]) +t1.start(); t2.start() +t1.join(); t2.join() +``` + +>
+> CPU times: user 501 ms, sys: 3.96 ms, total: 505 ms +> Wall time: 252 ms +>+ +```python +%%time + +# Note that the GIL-locked version is started first +t1 = Thread(target=fibonacci_gil, args=[N]) +t2 = Thread(target=fibonacci_nogil, args=[N]) +t1.start(); t2.start() +t1.join(); t2.join() +``` + +>
+> CPU times: user 533 ms, sys: 3.69 ms, total: 537 ms +> Wall time: 537 ms +>+ +Interestingly enough, Rust's borrow rules actually _prevent_ double-unlocking because the GIL handle +can't be transferred across threads: + +```rust +fn recursive_unlock(py: Python) -> PyResult<()> { + py.allow_threads(|| recursive_unlock(py)) +} +``` + +>
+> error[E0277]: `std::rc::Rc<()>` cannot be shared between threads safely +> --> src/lib.rs:38:8 +> | +> 38 | py.allow_threads(|| recursive_unlock(py)) +> | ^^^^^^^^^^^^^ `std::rc::Rc<()>` cannot be shared between threads safely +> | +> = help: within `pyo3::python::Python<'_>`, the trait `std::marker::Sync` is not implemented for `std::rc::Rc<()>` +>