The University of Edinburgh has announced the installation of an AI cluster consisting of four CS-3s using Cerebras’s 3rd generation of Wafer Scale Engine processors Operated by the Edinburgh Parallel ...

Abstract: MapReduce is one of the most classic and powerful parallel computing models in the field of big data. It is still active in the big data system ecosystem and is currently evolving towards ...

Official development repository for SUNDIALS - a SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. Pull requests are welcome for bug fixes and minor changes.

In a new study published by researchers at quantum computing company Quantinuum and collaborators from Caltech, Fermioniq, EPFL, and the Technical University of Munich, scientists have used Quantinuum ...

use Python’s native async library to break up non-CPU-bound tasks, and get started using parallel processing for heavier jobs in your Python programs. Also, check out the built-in async features ...

zenoh unifies data in motion, data in-use, data at rest and computations. It carefully blends traditional pub/sub with geo-distributed storages, queries and computations, while retaining a level of ...

Hoefler conducts research into the performance of parallel computer systems. His work has made a key contribution towards massively speeding up high-performance computing (HPC), improving efficiency ...

The language's parallel processing capabilities significantly reduce computation time, cutting down execution time by 56% compared to traditional methods. Python’s ability to distribute preprocessing ...

These are the authors: M.Sc. Bastian Hagedorn – main author, PhD student in the parallel and distributed systems group (PVS) at the University of Muenster, Prof. Sergei Gorlatch – Leader of the PVS ...