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UberCloud Voice July 2016

What Is High-Performance Computing and How Can Engineers Use It?

ClusterHigh-performance computing (HPC) has become increasingly more popular and important in the world of engineering. But defining what HPC is and figuring out how it can be deployed to aid designers can be tricky. And, honestly, it shouldn’t be that way. In this article, the author Kyle Maxey is going to present a clear definition of what HPC is, how it can be effectively used in engineering and what kind of HPC solutions are on the market today. By the end of this article, the reader should have a clear view of how HPC can help your engineering practice and what HPC options will best suit your needs. Read the Engineering.com article HERE.

New release FlyElephant 2.0 with Docker support

FlyElephantThe FlyElephant team announces the release of the platform FlyElephant 2.0, with following updates: internal expert community, collaboration on projects, public tasks, Docker and Jupyter support, a new file storage system which works with HPC clusters. Among the innovations are the following: Expert Community, Working together on projects, Public tasks, Docker support, Jupyter support, VNC support, The new file storage, Work with HPC clusters, and Registration via various social networks. See the announcement HERE.

ANSYS CFD and Microsoft Azure perform best HPC scalability in the cloud

Tejas ANSYS BlogJuly 25, 2016 – One of our cloud computing partners, Microsoft Azure, announced the addition of ANSYS computational fluid dynamics (CFD) solvers to their ISV ecosystem. Azure “Big Compute” now provides thousands of cores on demand to ANSYS customers to run their complex CFD simulation projects. These simulations will be backed by HPC infrastructure in Azure enabled by RDMA and InfiniBand technology available for Linux and Windows. “ANSYS and Microsoft Azure have been working closely on a Proof of Concept (POC) with a large customer to run ANSYS CFD workload on Azure,” said Ray Milhem, vice president of enterprise solutions at ANSYS. “The POC proved very successful and the data showed excellent scalability running ANSYS CFD up to 1024 cores.” Read Tejas Karmarkar’s blog HERE.

Video: PRACE Ada Lovelace Award for HPC for Dr. Zoe Cournia who led UberCloud Experiment #61

ZoeIn 2013, Dr. Zoe Cournai led the UberCloud Team 61 engineering cloud experiment resulting in her excellent case study on “Team 61: Molecular Dynamics of the Mutant PI3Kα Protein in the Cloud”, published in the 2014 UberCloud Compendium here: https://www.theubercloud.com/ubercloud-compendium-2014/. In this HPC Cloud experiment cloud based molecular dynamics (MD) simulations were used to gain insight into the oncogenic mechanism of two commonly expressed mutant PL3Kα by studying their conformational changes. Now, in July 2016, Dr. Zoe Cournai received the 2016 PRACE Ada Lovelace Award for High Performance Computing (HPC): http://insidehpc.com/2016/07/video-zoe-cournia-winner-of-the-prace-ada-lovelace-award-for-hpc/. Congratulations, Zoe !

Cloud use case: CAE Technology Services – CFD setup and computational time cut 50 percent

Team 187CAE Technology performed CFD analysis simulations for a top client, one of the world’s largest auto manufacturers. The project involved the intake manifold of a new V6 engine design. The car maker wanted CAE Technology to conduct what’s called a steady-state, incompressible flow analysis. “By using UberCloud ‘s ready-to-execute STAR-CCM+ application container, we simplified our software setup, and the Microsoft Azure HPC cluster based on Intel Xeon processors delivered a much faster analysis than our desktop workstations could,” said Velmurugan Patchamuthu, Founder & CEO of CAE Technology Services Inc. “Our approach—using UberCloud containers and Azure HPC—cut our overall time by 50 percent.” The details of this cloud use case can be found HERE.

Are we ready for the European Open Science Cloud?

Kimmo KoskiIn his recent blog post, Kimmo Koski, Managing Director of the CSC – IT Center for IT Science in Helsinki, Finland, and involved in many EU activities, is answering a few important questions about a European Open Science Cloud – EOSC:  Why do you need to create cloud on a European level?  Are national cloud efforts not enough?  Why do we need to talk about horizontal multidisciplinary cloud effort?  Isn’t domain specific cloud better since it can address the exact needs of communities?  The cloud development goes faster in US and China, so should we just wait and see what they provide? Read Kimmo’s answers and additional comments on the European Open Science Cloud HERE

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