XLA.jl
Julia on TPUs (by JuliaGPU)
pyhpc-benchmarks
A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket: (by dionhaefner)
XLA.jl | pyhpc-benchmarks | |
---|---|---|
1 | 6 | |
224 | 302 | |
- | - | |
10.0 | 3.2 | |
over 3 years ago | 4 months ago | |
Julia | Python | |
GNU General Public License v3.0 or later | The Unlicense |
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.
XLA.jl
Posts with mentions or reviews of XLA.jl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-13.
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If data science uses a lot of computational power, then why is python the most used programming language?
Julia can also use the same stuff that Python/Tensorflow use, to access the same hardware (e.g. Julia on TPUs https://github.com/JuliaTPU/XLA.jl).
pyhpc-benchmarks
Posts with mentions or reviews of pyhpc-benchmarks.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-12-05.
-
Supercharged high-resolution ocean simulation with Jax
True, but unfortunately Pytorch is not quite there yet when it comes to more complex benchmarks:
https://github.com/dionhaefner/pyhpc-benchmarks#example-resu...
JAX really is the only library that comes close to low-level code on CPU, almost always.
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[D] Does working with Tensorflow affect my chances of getting research internships?
https://github.com/dionhaefner/pyhpc-benchmarks begs to differ.
- GitHub - dionhaefner/pyhpc-benchmarks: A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python
- HPC Benchmarks for Python
- Pyhpc: Benchmarks for CPU and GPU of the most popular high-perf Python libs
What are some alternatives?
When comparing XLA.jl and pyhpc-benchmarks you can also consider the following projects:
serving - A flexible, high-performance serving system for machine learning models
tf-quant-finance - High-performance TensorFlow library for quantitative finance.
glow - Compiler for Neural Network hardware accelerators
pyopencl - OpenCL integration for Python, plus shiny features