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
January 16, 2019 by
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
April 19, 2018 by
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
February 8, 2018 by
“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
September 21, 2017 by
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
August 15, 2017 by
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
January 4, 2017 by
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.
