In this video from 2018 Swiss HPC Conference, Torsten Hoefler from (ETH) Zürich presents: Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis. “Deep Neural Networks ...

As someone who has spent the better part of two decades optimizing distributed systems—from early MapReduce clusters to ...

Breakthrough in 'distributed deep learning' MACH slashes time and resources needed to train computers for product searches Date: December 9, 2019 ...

In this video, Huihuo Zheng from Argonne National Laboratory presents: Data Parallel Deep Learning. The Argonne Training Program on Extreme-Scale Computing (ATPESC) provides intensive, two weeks of ...

On Oct. 16-17, some 60 Princeton graduate students and postdocs — along with a handful of undergraduates — explored the most widely used deep learning techniques for computer vision tasks and delved ...

ADELPHI, Md. -- A new algorithm is enabling deep learning that is more collaborative and communication-efficient than traditional methods. Army researchers developed algorithms that facilitate ...

It’s taken the idea of the distributed computing power of older projects such as SETI@home and the COVID-19 focussed Folding@home and applied it in the direction of this desire for deep learning ...

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.

This online research computing specialization introduces learners to the fundamentals of high performance and parallel computing and includes big data analysis, machine learning, parallel programming, ...