COMPUTING

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Databricks Expands EMEA Lakehouse Migration Solutions

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@databricks

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17 February 2023 15h33

We're excited to announce the expansion of our #BrickbuilderSolutions in EMEA! By combining the migration expertise of our partner ecosystem with #Lakehouse, our new solutions will help more businesses easily move to a single modern platform. Learn more https://
dbricks.co/3E6Isfv

XLA and Automatic Parallelization in JAX for Computation Speed

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17 February 2023 14h26

XLA & Automatic Parallelization It also supports XLA or Accelerated Linear Algebra, which is an optimizing compiler, designed specifically to increase the computation speed. And also supports Parallelization and can be done using "pmap()" https://
jax.readthedocs.io/en/latest/note
books/quickstart.html
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Automatic Vectorization with JAX vmap Function

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17 February 2023 14h26

Automatic Vectorization Vectorization helps faster code execution and Jax has an inbuilt function to do the same And can be done with using "vmap()" function Here are the detailed use cases and implementation of Vectorization. http://
jax.readthedocs.io/en/latest/_aut
osummary/jax.vmap.html#jax.vmap
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JAX vs NumPy: GPU and TPU Support Comparison

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17 February 2023 14h26

We have Numpy which is the fundamental python library for scientific computing. Why do we need Jax or How it differs from Numpy Numpy is only compatible with the CPU. JAX provides an implementation of NumPy with both GPU and TPU support. https://
github.com/google/jax

Jax: A Faster Python Library for Machine Learning and Computing

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17 February 2023 14h26

"Jax" is a python library for numerical computing, machine learning and is really faster than Numpy Here is why you should care about Jax and its really powerful features in Machine Learning: