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New Webinar Series – CAE Veteran Dennis Nagy on Addressing the Changing Role of Engineering Simulations – With a Focus on CAE Simulation in the Cloud

DennisCAE veteran Dennis Nagy from BeyondCAE is launching the new UberCloud “Thought Leadership” series of webinars from engineers for engineers. Until recently, many companies couldn’t afford buying their own expensive HPC equipment coming along with long procurement cycles, high total cost of ownership, and fast aging hardware technologies. Now, with HPC being available in the cloud, and roadblocks removed, this picture has changed dramatically. The goal of this webinar series is threefold: First, introduce webinar attendees to CAE cloud computing. Second, demonstrate to engineers the next generation of cloud technology for CAE and its user-friendliness. And third, encourage engineers to sign up for a hands-on UberCloud training. Dennis also briefly discusses the major HPC Cloud roadblock which have mostly been resolved over the last few years. Dennis is presenting this webinar together with UberCloud’s president Wolfgang Gentzsch. Get more information on the webinar and register HERE.

Technical Computing Hub UberCloud Receives Funding from Earlybird

Earlybird UberCloudLOS ALTOS, Calif., and ISTANBUL, Turkey, Jan. 26 — Today, UberCloud, the Silicon Valley based hub in the cloud for engineers and scientists to discover, try, and buy computing on demand, announces the closing of its Pre-A $1.7 million round lead by Earlybird Venture Capital. Roland Manger, co-founder and partner of Earlybird, joins the UberCloud Board of Directors. “UberCloud has created an entire cloud computing ecosystem for complex technical simulations, leveraging cloud infrastructure providers, developing and utilizing middleware container technology, and bringing on board established and proven application software providers, all for the benefit of a growing community of engineers and scientists that need to solve critical technical problems on demand,” said Roland Manger, co-founder and Partner at Earlybird. “While technical computing has been slow to adopt the benefits of the Cloud, we are convinced that UberCloud can be a catalyst for change.” Read the announcement HERE.

UberCloud Cites Big Progress in HPC Cloud Computing

After four years, 200 cloud experiments and 80 CAE case studies later, we are now able to measure cloud computing progress, quite objectively. Looking back four years at our first 50 cloud experiments, 26 of them failed or didn’t finish, and the average duration of the successful ones was about three months. Four years later, in 2016, looking at our last 50 cloud experiments, none failed; and the average duration of these experiments is now just about three days. This article summarizes major findings. We also present a discussion of roadblocks – such a security, software licensing,porting application software to the cloud, total cost, cloud complexity, and losing control over you assets in the cloud – and how they have been resolved, and offers three examples from the latest 2016 Compendium of HPC cloud case studies. Read the full HPCwire Feature story HERE.

CAE Containers can help energy, oil and gas companies accelerate adoption of cloud-based HPC.

oil-pumpMore companies are adopting cloud-based high performance computing (HPC), especially in industries that require significant computational power. The energy, oil and gas markets are no exception. After all, they rely on advanced computer-aided engineering (CAE), advanced data analytics, seismic processing, and other data- and computationally-demanding applications. But implementing cloud-based HPC will require new approaches that deliver greater flexibility and ease deployments. One such solution? Containers. And what’s the advantage of containers for HPC? With traditional HPC systems, compute, network, power, data, and any associated technologies need to be architected and developed, designed and implemented. With a container-based solution that’s running in the cloud, only the application needs to be developed, as the infrastructure can be agnostic and always available. That may seem idyllic, but read more HERE.

Amazon AWS Outlines HPC Cloud User Trends, Looks at Machine Learning & Deep Learning in the Cloud

The Next Platform

Nicole Hemsoth from The Next Platform discusses the projected momentum for AWS’ new FPGAs in the cloud with Deepak Singh, general manager of container and HPC projects at Amazon Web Services. In the second half of the interview, they delved into the current state of high performance computing on Amazon’s cloud. While the company tends to offer generalizations versus specific breakdowns of “typical” workloads for different HPC application types, the insight reveals a continued emphasis on pushing new instances to feed both HPC and machine learning, continued drive to push ISVs to expand license models, and continued work to make running complex workflows more seamless. Read Nicole’s article with Deepak Singh HERE.

Comparing Amazon AWS, Google Cloud, and Microsoft Azure

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Comparing Amazon AWS, Google Cloud, and Microsoft Azure

 

Are you shopping for Public Cloud services?

 

A new Psite gives a service & feature level mapping between the 3 major public clouds: Amazon Web Services, Microsoft Azure & Google Cloud. Published by Ilyas F, a Cloud Solution Architect at Xebia Group, the Peference manual to help anyone to quickly learn the alternate features and services between these clouds.

 

The Comparison chart lists the following types of features, services, and domain spaces: Compute, Storage, Database, Migration Services, Networking & Content Delivery, Developer Tools, Management Tools, Security, Identity, & Compliance, Big Data & Advanced Analytics, Artificial Intelligence, Mobile Services, Application Services, Business Productivity,Internet of Things, Game Development, and Development & Testing. Read the details in InsideHPC.

 

Do you need help deciding which cloud is right for you? Schedule a free expert consultation with us and we can help you decide

Download the New 2016 Compendium of Engineering Cloud Case Studies

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The New 2016 Compendium of Engineering Cloud Case Studies – sponsored by Digital Engineering, Hewlett Packard Enterprise, and Intel – is an invaluable resource for engineers, scientists, managers and executives who believe in the strategic importance of Technical Computing as a Service, in the Cloud, for their organization. It is a collection of 19 selected real-life case studies written by the participants of the UberCloud HPC Experiment. Among these case studies you will find scenarios that resonate with your own situation. You will benefit from the candid descriptions of problems encountered, problems solved, and lessons learned. Projects covered are in fields of Computer Aided Engineering (CAE), such as Computational Fluid Dynamics (CFD) and Structural Analysis (FEA). Case studies are about an engine intake manifold, airbag simulation, ship barehull resistance, wind turbines, airflow within a nasal cavity, thermal modelling of a reactor, implantable antennas, and more, to name a few. You can download the Compendium HERE.

Webinar January 10, 2017: Turbomachinery CFD in the Cloud – An Easy Guide to Access and Use OpenFOAM for Turbomachinery on Demand, with a Live Demo in the Cloud

TurboCFD in CloudTurbomachinery CFD is an open-source workflow based on OpenFOAM®, covering the complete process from CAD data to CFD analysis to engineering results. CFD Support turbomachinery cloud products can be accesses on the UberCloud Marketplace. Based on many engineering cloud experiments, in this webinar we will present our experience, lessons learned and recommendations on how to best use cloud computing to accelerate your turbomachinery CFD design and product development, scaling up to hundreds of cores, resulting in ten to hundred-fold speed-ups, allowing for complex geometries with fine meshes processed in less time. We will demonstrate these advantages with a real-live case study from our Team 183 about “Radial Fan CFD Simulation in the Azure Cloud”, in an UberCloud software container on a CESNET cluster in Prague as part of the EGI Cloud infrastructure. To engineers, this cloud resource looks like your home desktop computer, no need to learn anything new, and still your OpenFOAM turbomachinery job and the data can be accessed and used in the same way, at your fingertips. Please register for the webinar on January 10, 2017 HERE

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