nanobind
Disruptor
nanobind | Disruptor | |
---|---|---|
11 | 30 | |
2,042 | 17,029 | |
- | 0.4% | |
9.6 | 5.4 | |
4 days ago | 4 months ago | |
C++ | Java | |
BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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.
nanobind
-
Progress on No-GIL CPython
Take a look at https://github.com/wjakob/nanobind
> More concretely, benchmarks show up to ~4× faster compile time, ~5× smaller binaries, and ~10× lower runtime overheads compared to pybind11.
-
Advanced Python Mastery – A Course by David Beazley
People should not take that an endorsement of Swig.
Please use ctypes, cffi or https://github.com/wjakob/nanobind
Beazley himself is amazed that it (Swig) is still in use.
- Swig – Connect C/C++ programs with high-level programming languages
- Nanobind: Tiny and efficient C++/Python bindings
-
Create Python bindings for my C++ code with PyBind11
Nanobind made by the creator of PyBind11, it has a similar interface, but it takes leverage of C++17 and it aims to have more efficient bindings in space and speed.
- Nanobind – Seamless operability between C++17 and Python
-
Cython Is 20
I would recommend using NanoBind, the follow up of PyBind11 by the same author (Wensel Jakob), and move as much performance critical code to C or C++. https://github.com/wjakob/nanobind
If you really care about performance called from Python, consider something like NVIDIA Warp (Preview). Warp jits and runs your code on CUDA or CPU. Although Warp targets physics simulation, geometry processing, and procedural animation, it can be used for other tasks as well. https://github.com/NVIDIA/warp
Jax is another option, by Google, jitting and vectorizing code for TPU, GPU or CPU. https://github.com/google/jax
- GitHub - wjakob/nanobind: nanobind — Seamless operability between C++17 and Python
Disruptor
-
Gnet is the fastest networking framework in Go
https://lmax-exchange.github.io/disruptor/#_what_is_the_disr.... Unfortunately IIUC writing this in Go still prevents the spin-locked acceptor thread from achieving the kind of performance you could get in a non-GC language, unless you chose to disable GC, so I'd guess Envoy is still faster.
https://gnet.host/docs/quickstart/ it's nice that you can use this simply though. Envoy is kind of tricky to setup with custom filters, so most of the time it's just a standalone binary.
[0] https://blog.envoyproxy.io/envoy-threading-model-a8d44b92231...
[1] https://lmax-exchange.github.io/disruptor/#_what_is_the_disr...
-
A lock-free ring-buffer with contiguous reservations (2019)
See also the Java LMAX Disruptor https://github.com/LMAX-Exchange/disruptor
I've built a similar lock-free ring buffer in C++11 https://github.com/posterior/loom/blob/master/doc/adapting.m...
-
JEP Draft: Deprecate Memory-Access Methods in Sun.misc.Unsafe for Removal
"Why we chose Java for our High-Frequency Trading application"
https://medium.com/@jadsarmo/why-we-chose-java-for-our-high-...
LMAX Disruptor customers
https://lmax-exchange.github.io/disruptor/
Among many other examples.
-
LMAX Disruptor – High Performance Inter-Thread Messaging Library
Current documentation
https://lmax-exchange.github.io/disruptor/
-
Progress on No-GIL CPython
LMAX Disruptor has on their wiki that average latency to send a message from one thread to another at 53 nanoseconds. For comparison a mutex is like 25 nanoseconds and more if Contended but a mutex is point to point synchronization.
The great thing about it is that multiple threads can receive the same message without much more effort.
https://github.com/LMAX-Exchange/disruptor/wiki/Performance-...
https://gist.github.com/rmacy/2879257
I am dreaming of language that is similar to Smalltalk that stays single threaded until it makes sense to parallise.
I am looking for problems to parallelism that are not big data. Parallelism is like adding more cars to the road rather than increasing the speed of the car. But what does a desktop or mobile user need to do locally that could take advantage of the mathematical power of a computer? I'm still searching.
- Disruptor 4.0.0 Released
-
Anything can be a message queue if you use it wrongly enough
Database config should be two connection strings, 1 for the admin user that creates the tables and anther for the queue user. Everything else should be stored in the database itself. Each queue should be in its own set of tables. Large blobs may or may not be referenced to an external file.
Shouldn't a message send be worst case a CAS. It really seems like all the work around garbage collection would have some use for in-memory high speed queues.
Are you familiar with the LMAX Disruptor? Is is a Java based cross thread messaging library used for day trading applications.
https://lmax-exchange.github.io/disruptor/
-
Any library you would like to recommend to others as it helps you a lot? For me, mapstruct is one of them. Hopefully I would hear some other nice libraries I never try.
Disruptor for inter-thread messaging
-
Measuring how much Rust's bounds checking actually costs
I have never worked in any industries where a perf margin was that small. It is funny, in HFT there are folks using Lmax (Java) and then you have folks writing their own TCP/IP stacks on FPGAs to do trading.
What are some alternatives?
pybind11 - Seamless operability between C++11 and Python
JCTools
awesome-cython - A curated list of awesome Cython resources. Just a draft for now.
Agrona - High Performance data structures and utility methods for Java
Nuitka - Nuitka is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11. You feed it your Python app, it does a lot of clever things, and spits out an executable or extension module.
fastutil - fastutil extends the Java™ Collections Framework by providing type-specific maps, sets, lists and queues.
matplotlibcpp17 - Alternative to matplotlibcpp with better syntax, based on pybind
MPMCQueue.h - A bounded multi-producer multi-consumer concurrent queue written in C++11
epython - EPython is a typed-subset of the Python for extending the language new builtin types and methods
Eclipse Collections - Eclipse Collections is a collections framework for Java with optimized data structures and a rich, functional and fluent API.
avendish - declarative polyamorous cross-system intermedia objects
Javolution