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SingularityPRO comes to Google Cloud

Today Sylabs announced a multi-phase collaboration with Google Cloud as a technology partner. Aimed at systematically addressing enterprise requirements in a cloud-native fashion, the first phase of the collaboration will be based upon availability of Sylabs’ SingularityPRO via the Google Cloud Platform Marketplace. “Singularity is a widely adopted container runtime that implements a unique security model to mitigate privilege escalation risks, and provides a platform to capture a complete application environment into a single file.”

Atos Opens AI Laboratory in France with the Google Cloud

Today Atos inaugurated a new AI laboratory in France. Set up as part of the global partnership between Atos and Google Cloud, the laboratory will enable clients, businesses and public organizations to identify practical cases, for which AI could provide innovative and effective solutions. “In order for France to continue to play a key role in the information space, it has to invest heavily in artificial intelligence and new technologies,” said Thierry Breton, Chairman and CEO of Atos. “Beyond economic development, being able to offer technological excellence while protecting European data is a matter of sovereignty. With this joint laboratory between Atos and Google Cloud, we are enabling the adoption of artificial intelligence by our clients by offering them the best technologies and the highest level of security for their data processing, all within a clearly defined European regulatory framework. As such, Atos combines economic and technological development with sovereignty, compliance and security and helps to design a secure and valued European information space.”

E-CAS Project to Explore Clouds for Acceleration of Science

Can the Cloud power ground-breaking research? A new NSF-funded research project aims to provide a deeper understanding of the use of cloud computing in accelerating scientific discoveries. “First announced in 2018, the Exploring Clouds for Acceleration of Science (E-CAS) project has now selected the six research proposals to explore how scientific workflows can leverage advancements in real-time analytics, artificial intelligence, machine learning, accelerated processing hardware, automation in deployment and scaling, and management of serverless applications for a wider range of science.”

NVIDIA T4 GPUs Come to Google Cloud for High Speed Machine Learning

Today the Google Cloud announced Public Beta availability of NVIDIA T4 GPUs for Machine Learning workloads. Starting today, NVIDIA T4 GPU instances are available in the U.S. and Europe as well as several other regions across the globe, including Brazil, India, Japan and Singapore. “The T4 is the best GPU in our product portfolio for running inference workloads. Its high-performance characteristics for FP16, INT8, and INT4 allow you to run high-scale inference with flexible accuracy/performance tradeoffs that are not available on any other accelerator.”

Universities step up to Cloud Bursting

In this special guest feature, Mahesh Pancholi from OCF writes that many of universities are now engaging in cloud bursting and are regularly taking advantage of public cloud infrastructures that are widely available from large companies like Amazon, Google and Microsoft. “By bursting into the public cloud, the university can offer the latest and greatest technologies as part of its Research Computing Service for all its researchers.”

Big 3 Cloud Providers join with NSF to Support Data Science

“NSF’s participation with major cloud providers is an innovative approach to combining resources to better support data science research,” said Jim Kurose, assistant director of NSF for Computer and Information Science and Engineering (CISE). “This type of collaboration enables fundamental research and spurs technology development and economic growth in areas of mutual interest to the participants, driving innovation for the long-term benefit of our nation.”

NVIDIA P100 GPUs come to Google Cloud Platform

Today the good folks at the Google Compute Platform announced the availability of NVIDIA GPUs in the Cloud for multiple geographies. Cloud GPUs can accelerate workloads such as machine learning training and inference, geophysical data processing, simulation, seismic analysis, molecular modeling, genomics and many more high performance compute use cases. “Today, we’re happy to make some massively parallel announcements for Cloud GPUs. First, Google Cloud Platform (GCP) gets another performance boost with the public launch of NVIDIA P100 GPUs in beta.

Microsoft Acquires Cycle Computing

Today Microsoft announced it has acquired Cycle Computing, a software company focused on making cloud computing resources more readily available for HPC workloads. “Now supporting InfiniBand and accelerated GPU computing, Microsoft Azure looks to be a perfect home for Cycle Computing, which started its journey with software for aggregating compute resources at AWS. The company later added similar capabilities for Azure and Google Cloud.”

New Site Lists all Comparable Features from AWS, Azure, and Google Cloud

Are you shopping for Public Cloud services? A new Public Cloud Services Comparison site gives a service & feature level mapping between the 3 major public clouds: Amazon Web Service, Microsoft Azure & Google Cloud. Published by Ilyas F, a Cloud Solution Architect at Xebia Group, the Public Cloud Services Comparison is a handy reference manual to help anyone to quickly learn the alternate features & services between clouds.