In this video from EuroPython 2019, Pierre Glaser from INRIA presents: Parallel computing in Python ... These performance improvements will be leveraged by distributed data science frameworks such as ...

He has made deep and wide-ranging contributions to many areas of parallel computing including programming languages, compilers, and runtime systems for multicore, manycore and distributed computers.

The company also announced the general availability of its service, which allows developers to scale data and AI applications developed on a laptop to run on AWS and Google Cloud in a distributed ...