Tejas Karmarkar from Microsoft presented this talk at SC15. “Azure provides on-demand compute resources that enable you to run large parallel and batch compute jobs in the cloud. Extend your on-premises HPC cluster to the cloud when you need more capacity, or run work entirely in Azure. Scale easily and take advantage of advanced networking features such as RDMA to run true HPC applications using MPI to get the results you want, when you need them.”
“Modeling and simulation have been the primary usage of high performance computing (HPC). But the world is changing. We now see the need for rapid, accurate insights from large amounts of data. To accomplish this, HPC technology is repurposed. Likewise the location where the work gets done is not entirely the same either. Many workloads are migrating to massive cloud data centers because of the speed of execution. In this panel, leaders in computing will share how they, and others, integrate tradition and innovation (HPC technologies, Big Data analytics, and Cloud Computing) to achieve more discoveries and drive business outcomes.”
“Our vision is to deliver accelerated graphics and high performance computing to any connected device, regardless of location,” said Jen-Hsun Huang, co-founder and CEO of NVIDIA. “We are excited to collaborate with Microsoft Azure to give engineers, designers, content creators, researchers and other professionals the ability to visualize complex, data-intensive designs accurately from anywhere.”
In this video from the 2015 OFS Developer’s Workshop, Tom Talpey from Microsoft presents: Microsoft Update on RDMA.
In this podcast, the Radio Free HPC team discuss the possibility of a future where the Big 3 (Amazon, Google, and Microsoft) figure out that Cloud is not profitable and pull the plug. If that Cloud Apocalypse sounds far fetched, a look at recent AWS revenue numbers may prompt you to stock up your bomb shelter.
“Our belief is that trying to build a quantum machine by controlling electron spin and using surface codes is like trying to build a computer using vacuum tubes. Labs all over the world can do that, but you’ll never be able to scale up.”