Sign up for our newsletter and get the latest HPC news and analysis.
Send me information from insideHPC:

Video: Scalable Deep Learning with Microsoft Cognitive Toolkit (CNTK)

“Microsoft AI researchers are striving to create intelligent machines that complement human reasoning and enrich human experiences and capabilities. At the core, is the ability to harness the explosion of digital data and computational power with advanced algorithms that extend the ability for machines to learn, reason, sense and understand—enabling collaborative and natural interactions between machines and humans.”

Interview: Hot Interconnects Conference to Focus on Next-Generation Networks

The Hot Interconnects Conference is coming up Aug. 28-30 in Santa Clara. To learn more, we caught up with Program Chairs Ryan Grant and Jitu (Jitendra) Padhye. “Hot Interconnects brings together members of the industrial, academic and broader research community to unveil the very latest advances in network technologies as well as to discuss ideas for future generation interconnects. Unlike other conferences, Hot Interconnects is focused on only the latest most topical subjects and concentrates on technologies that will be available for deployment in the near future.”

Video: Towards Quantum High Performance Computing

“Following an introduction to the exceptional computational power of quantum computers using analogies with classical high performance computing systems, I will discuss real-world application problems that can be tackled on medium scale quantum computers but not on post exa-scale classical computers. I will motivate hardware software co-design of quantum accelerators to classical supercomputers and the need for educating a new generation of quantum software engineers with knowledge both in quantum computing and in high performance computing.”

Jennifer Chayes from Microsoft Research to Keynote ISC 2017

Today ISC 2017 announced that data scientist, Prof. Dr. Jennifer Tour Chayes from Microsoft Research will give the opening keynote at the conference. “I’ll discuss in some detail two particular applications: the very efficient machine learning algorithms for doing collaborative filtering on massive sparse networks of users and products, like the Netflix network; and the inference algorithms on cancer genomic data to suggest possible drug targets for certain kinds of cancer,” explains Chayes.

Video: A Hybrid Approach to Strongly Correlated Materials

Matthias Troyer frin ETH Zurich presented this talk at a recent Microsoft Research event. “Given limitations to the scaling for simulating the full Coulomb Hamiltonian on quantum computers, a hybrid approach – deriving effective models from density functional theory codes and solving these effective models by quantum computers seem to be a promising way to proceed for calculating the electronic structure of correlated materials on a quantum computer.”