Abstract: We present mpi4py.futures, a lightweight, asynchronous task execution framework targeting the Python programming language and using the Message Passing Interface (MPI) for interprocess ...

Tired of out-of-memory errors derailing your data analysis? There's a better way to handle huge arrays in Python.

Overview: Prior knowledge of the size and composition of the Python dataset can assist in making informed choices in programming to avoid potential performance ...

This article is adapted from an edition of our Off the Charts newsletter originally published in October 2021. Off the Charts is a weekly, subscriber-only guide to The Economist’s award-winning data ...

Data scientists and analysts rely heavily on Python libraries to extract insights from complex data sets. Pandas and Dask are two popular choices, but they cater to different use cases and ...

One of the long-standing bottlenecks for researchers and data scientists is the inherent limitation of the tools they use for numerical computation. NumPy, the go-to library for numerical operations ...

In computational chemistry, molecules are often represented as molecular graphs, which must be converted into multidimensional vectors for processing, particularly in machine learning applications.

I am training a LightGBM model in a distributed cluster setting using the Dask interface. When I set the early_stopping_rounds parameter, it causes the training job to hang indefinitely whenever the ...

Abstract: Python is a high level language that is used by scientists for numeric computations. However, the performance of the language can be a hindrance when scaling to larger data sets, requiring ...