mpi4jax
Zero-copy MPI communication of JAX arrays, for turbo-charged HPC applications in Python :zap: (by PhilipVinc)
pyhpc-benchmarks
A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket: (by dionhaefner)
| mpi4jax | pyhpc-benchmarks | |
|---|---|---|
| 1 | 6 | |
| 371 | 301 | |
| 3.2% | - | |
| 6.7 | 3.2 | |
| 18 days ago | 4 months ago | |
| Python | Python | |
| MIT License | 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.
mpi4jax
Posts with mentions or reviews of mpi4jax.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-02-03.
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[D] Jax (or other libraries) when not using GPUs/TPUs but CPUs.
I've seen a couple of posts of folks using JAX for scientific computing (e.g. physics) workloads without much issue. The parallel primitives work just as well across multiple CPUs as they do on accelerators. If you're on a cluster, also worth looking into https://github.com/PhilipVinc/mpi4jax.
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 mpi4jax and pyhpc-benchmarks you can also consider the following projects:
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
tf-quant-finance - High-performance TensorFlow library for quantitative finance.
extending-jax - Extending JAX with custom C++ and CUDA code
pyopencl - OpenCL integration for Python, plus shiny features