XLA.jl
Julia on TPUs (by JuliaGPU)
runtime
A performant and modular runtime for TensorFlow (by tensorflow)
| XLA.jl | runtime | |
|---|---|---|
| 1 | 2 | |
| 224 | 745 | |
| - | 0.1% | |
| 10.0 | 9.6 | |
| over 3 years ago | 9 days ago | |
| Julia | C++ | |
| GNU General Public License v3.0 or later | 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.
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.
-
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).
runtime
Posts with mentions or reviews of runtime.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-13.
-
If data science uses a lot of computational power, then why is python the most used programming language?
For reference: In Tensorflow and JAX, for example, the tensor gets compiled to the intermediate XLA format (https://www.tensorflow.org/xla), then passed to the XLA complier (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/compiler/xla/service) or the new TFRT runtime (https://github.com/tensorflow/runtime/blob/master/documents/tfrt_host_runtime_design.md), or some more esoteric hardware (https://github.com/pytorch/glow).
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PyTorch vs. TensorFlow in Academic Papers
what are your thoughts on https://github.com/tensorflow/runtime ?
What are some alternatives?
When comparing XLA.jl and runtime you can also consider the following projects:
serving - A flexible, high-performance serving system for machine learning models
glow - Compiler for Neural Network hardware accelerators
elegy - A High Level API for Deep Learning in JAX
flax - Flax is a neural network library for JAX that is designed for flexibility.
julia - The Julia Programming Language
pyhpc-benchmarks - A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket:
tensorflow - An Open Source Machine Learning Framework for Everyone