distributed and parallel computing”—Python isn’t fast or convenient enough. Julia aims to give scientists and data analysts not only fast and convenient development, but also blazing ...

From the outside, Dask looks a lot like Ray. It, too, is a library for distributed parallel computing in Python, with a built-in task scheduling system, awareness of Python data frameworks like ...

Anyscale, a startup founded by a team out of UC Berkeley that created the Ray open-source Python framework for running distributed computing projects, has raised $40 million. It plans to use the ...

As Python is the language of choice for most ... so after about a year Dask was extended to work in a distributed computing environment which has more or less the same scaling properties as ...

but without the need for advanced skills in distributed computing. “It’s not like they have to relearn everything they know about computer science and software,” he says. “If they have some Python ...

In this video from the 2018 Blue Waters Symposium, Aaron Saxton from NCSA presents a tutorial entitled “Machine Learning with Python: Distributed Training and ... office at the National Center for ...

With distributed computing, applications are created by ... the effectiveness of automation frameworks such as a Puppet, Chef and even Python are limited. In this case, these tools are used ...

Distributed computing allows components of software ... Ray allows users to transform sequentially running Python code into a distributed application with minimal code changes.

Distributed computing erupted onto the scene in 1999 with the release of SETI@home, a nifty program and screensaver (back when people still used those) that sifted through radio telescope signals ...