nogil
Graal
nogil | Graal | |
---|---|---|
31 | 156 | |
2,854 | 19,807 | |
- | 0.5% | |
5.7 | 10.0 | |
2 months ago | 3 days ago | |
Python | Java | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
nogil
- Proof-of-Concept Multithreaded Python Without the GIL
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Our Plan for Python 3.13
This might be a dumb question, but why would removing the GIL break FFI? Is it just that existing no-GIL implementations/proposals have discarded/ignored it, or is there a fundamental requirement, e.g. C programs unavoidably interact directly with the GIL? I know that the C-API is only stable between minor releases [0] compiled in the same manner [1], so it's not like the ecosystem is dependent upon it never changing.
I cannot seem to find much discussion about this. I have found a no-GIL interpreter that works with numpy, scikit, etc. [2][3] so it doesn't seem to be a hard limit. (That said, it was not stated if that particular no-GIL implementation requires specially built versions of C-API libs or if it's a drop-in replacement.)
[0]: https://docs.python.org/3/c-api/stable.html#c-api-stability
[1]: https://docs.python.org/3/c-api/stable.html#platform-conside...
[2]: https://github.com/colesbury/nogil
[3]: https://discuss.python.org/t/pep-703-making-the-global-inter...
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Real Multithreading Is Coming to Python
https://github.com/colesbury/nogil does manage to get rid of the GIL, but it's not certain to make it into Python core. The main problem is the amount of existing libraries that depend on the existence of the GIL without realizing it - breaking those would be extremely disruptive.
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[D] The hype around Mojo lang
CPython is also investigating the removal of the GIL (PEP703, nogil). I think requiring the GIL is a wider thing that libraries will need to address anyway. But also, for the same reason as above I'd be surprised if the Modular team thought that saying "you can run all your python code unchanged" was a good idea if there was a secret "except for code that uses numpy" muttered under the breath.
- PEP 684 was accepted – Per-interpreter GIL in Python 3.12
- PEP 703 – Making the Global Interpreter Lock Optional in CPython
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Python 3.11.0 final is now available
I'm worried about the speedup
My understanding is that it's based on the most recent attempt to remove the GIL by Sam Gross
https://github.com/colesbury/nogil
In addition to some ways to try to not have nogil have as much overhead he added a lot of unrelated speed improvements so that python without the gil would still be faster not slower in single thread mode. They seem to have merged those performance patches first that means if they add his Gil removal patches in say python 3.12 it will still be substantially slower then 3.11 although faster then 3.10. I hope that doesn't stop them from removing the gil (at least by default)
- Removed the GIL back in 1996 from Python 1.4, primarily to create a re-entrant Python interpreter.
- I Tried Removing Python's GIL Back in 1996
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Faster CPython 3.12 Plan
Looks like it's still active to me:
https://github.com/colesbury/nogil/
Graal
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Java 23: The New Features Are Officially Announced
Contrary to what vocal Kotlin advocates might believe, Kotlin only matters on Android, and that is thanks to Google pushing it no matter what.
https://spectrum.ieee.org/the-top-programming-languages-2023
https://snyk.io/reports/jvm-ecosystem-report-2021/
And even so, they had to conceed Android and Kotlin on their own, without the Java ecosystem aren't really much useful, thus ART is now updatable via Play Store, and currently supports OpenJDK 17 LTS on Android 12 and later devices.
As for your question regarding numbers, mostly Java 74.6%, C++ 13.7%, on the OpenJDK, other JVM implementations differ, e.g. GraalVM is mostly Java 91.8%, C 3.6%.
https://github.com/openjdk/jdk
https://github.com/oracle/graal
Two examples from many others, https://en.wikipedia.org/wiki/List_of_Java_virtual_machines
- FLaNK Stack 05 Feb 2024
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Apple releases Pkl – onfiguration as code language
Pkl was built using the GraalVM Truffle framework. So it supports runtime compilation using Futurama Projections. We have been working with Apple on this for a while, and I am quite happy that we can finally read the sources!
https://github.com/oracle/graal/tree/master/truffle
Disclaimer: graalvm dev here.
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Live Objects All the Way Down: Removing the Barriers Between Apps and VMs
That's pretty interesting. It's not as aggressive as Bee sounds, but the Espresso JVM is somewhat similar in concept. It's a full blown JVM written in Java with all the mod cons, which can either be compiled ahead of time down to memory-efficient native code giving something similar to a JVM written in C++, or run itself as a Java application on top of another JVM. In the latter mode it obviously doesn't achieve top-tier performance, but the advantage is you can easily hack on it using all the regular Java tools, including hotswapping using the debugger.
When run like this, the bytecode interpreter, runtime system and JIT compiler are all regular Java that can be debugged, edited, explored in the IDE, recompiled quickly and so on. Only the GC is provided by the host system. If you compile it to native code, the GC is also written in Java (with some special conventions to allow for convenient direct memory access).
What's most interesting is that Espresso isn't a direct translation of what a classical C++ VM would look like. It's built on the Truffle framework, so the code is extremely high level compared to traditional VM code. Details like how exactly transitions between the interpreter/compiled code happen, how you communicate pointer maps to the GC and so on are all abstracted away. You don't even have to invoke the JIT compiler manually, that's done for you too. The only code Espresso really needs is that which defines the semantics of the Java bytecode language and associated tools like the JDWP debugger protocol.
https://github.com/oracle/graal/tree/master/espresso
This design makes it easy to experiment with new VM features that would be too difficult or expensive to implement otherwise. For example it implements full hotswap capability that lets you arbitrarily redefine code and data on the fly. Espresso can also fully self-host recursively without limit, meaning you can achieve something like what's described in the paper by running Espresso on top of Espresso.
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Crash report and loading time
I'm also using GraalVM if that's of any help.
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Quarkus 3.4 - Container-first Java Stack: Install with OpenJDK 21 and Create REST API
Quarkus is one of Java frameworks for microservices development and cloud-native deployment. It is developed as container-first stack and working with GraalVM and HotSpot virtual machines (VM).
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Level-up your Java Debugging Skills with on-demand Debugging
Apologies, I didn't mean to imply DCEVM went poof, just that I was sad it didn't make it into OpenJDK so one need not do JDK silliness between the production one and the "debugging one" since my experience is that's an absolutely stellar way to produce Heisenbugs
And I'll be straight: Graal scares me 'cause Oracle but I just checked and it looks to the casual observer that it's straight-up GPLv2 now so maybe my fears need revisiting: https://github.com/oracle/graal/blob/vm-23.1.0/LICENSE
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Rust vs Go: A Hands-On Comparison
> to be compiled to a single executable is a strength that Java does not have
I think this is very outdated claim: https://www.graalvm.org/
- Leveraging Rust in our high-performance Java database
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Java 21 makes me like Java again
https://github.com/oracle/graal/issues/7182
What are some alternatives?
hpy - HPy: a better API for Python
Liberica JDK - Free and 100% open source Progressive Java Runtime for modern Javaâ„¢ deployments supported by a leading OpenJDK contributor
mypyc - Compile type annotated Python to fast C extensions
Adopt Open JDK - Eclipse Temurinâ„¢ build scripts - common across all releases/versions
numpy - The fundamental package for scientific computing with Python.
awesome-wasm-runtimes - A list of webassemby runtimes
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
SAP Machine - An OpenJDK release maintained and supported by SAP
python-feedstock - A conda-smithy repository for python.
maven-jpackage-template - Sample project illustrating building nice, small cross-platform JavaFX or Swing desktop apps with native installers while still using the standard Maven dependency system.
sbcl - Mirror of Steel Bank Common Lisp (SBCL)'s official repository
wasmer - 🚀 The leading Wasm Runtime supporting WASIX, WASI and Emscripten