faster-python-with-taichi
By taichi-dev
taichi_benchmark
By taichi-dev
Our great sponsors
faster-python-with-taichi | taichi_benchmark | |
---|---|---|
3 | 4 | |
79 | 34 | |
- | - | |
0.0 | 4.5 | |
over 1 year ago | about 1 year ago | |
Python | Python | |
- | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
faster-python-with-taichi
Posts with mentions or reviews of faster-python-with-taichi.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-08-19.
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Faster reaction-diffusion simulation in Python
The source code is here. Reaction-diffusion is the third example in the repo, apart from the other two cases where the package speeds up Python code. I also wrote a detailed explanation and you can skip to the third example.
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Accelerate Python code 100x by import taichi as ti
You can refer to the source code of three examples comparing Taichi with Python here.
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Accelerate Python code 100x using Taichi Lang
A shortcut to the source code of the three cases: https://github.com/taichi-dev/faster-python-with-taichi.
taichi_benchmark
Posts with mentions or reviews of taichi_benchmark.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-08-19.
- Taichi Lang: A high-performance parallel programming language embedded in Python
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I compared the performance of numerical computations facilitated by different acceleration toolkits... And here are the results!
In fact, Taichi's compiler relies on heavy underlying engineering to enable high performance. In the aforementioned code snippet, the summation is actually an atomic operation, which cannot be parallelized and is thus subject to limited operation efficiency. The most commonly used method of parallel computing optimization in vector summation is reduction, which is one of the must-have skills to learn parallel computing. The benchmark report concludes that, thanks to automatic reduction optimization implemented by its compiler, Taichi achieves a performance comparable to manually implemented CUB and way better than Numba.
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Accelerate Python code 100x by import taichi as ti
Sure, here are some benchmarks that could be helpful: https://github.com/taichi-dev/taichi_benchmark
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ETH Zürich uses Taichi Lang in its Physically-based Simulation course (AS 21)
Some are uncertain about Taichi Lang's performance against other frameworks such as CUDA, and would require a comprehensive benchmarking report. Actually, we published a systematic benchmarking report when we released Taichi Lang v1.0.0. Taichi has more or less comparable performance to CUDA. But, for sure, you will have much fewer lines of code with Taichi Lang!
What are some alternatives?
When comparing faster-python-with-taichi and taichi_benchmark you can also consider the following projects:
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
taichi - Productive, portable, and performant GPU programming in Python.
Pyjion - Pyjion - A JIT for Python based upon CoreCLR
awesome-taichi - A curated list of awesome Taichi applications, courses, demos and features.