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Using OpenStack to Manage a Data Analytics HPC Cluster at PSC

“This talk will discuss the plans to use OpenStack to manage and automate dynamically changing an environment to provide users a highly re-configurable software environment with access to a large number of operating systems and software packages on the “Bridges system.” It will feature elements of OpenStack related to bare-metal booting, network provisioning, container management, storage, and scheduling nodes to match the workloads of the users.”

Podcast: Big Data on the Wrangler Supercomputer

In this TACC podcast, Niall Gaffney from the Texas Advanced Computing Center discusses the Wrangler supercomputer for data-intensive computing. “We went to propose to build Wrangler with (the data world) in mind. We kept a lot of what was good with systems like Stampede, but then added new things to it like a very large flash storage system, a very large distributed spinning disc storage system, and high speed network access to allow people who have data problems that weren’t being fulfilled by systems like Stampede and Lonestar to be able to do those in ways that they never could before.”

Dell Panel on the Convergence of HPC, Big Data, and Cloud

“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.”

PSC’s Bridges Supercomputer Brings HPC to a New Class of Users

The democratization of HPC got a major boost last year with the announcement of an NSF award to the Pittsburgh Supercomputing Center. The $9.65 million grant for the development of Bridges, a new supercomputer designed to serve a wide variety of scientists, will open the door to users who have not had access to HPC until now. “Bridges is designed to close three important gaps: bringing HPC to new communities, merging HPC with Big Data, and integrating national cyberinfrastructure with campus resources. To do that, we developed a unique architecture featuring Hewlett Packard Enterprise (HPE) large-memory servers including HPE Integrity Superdome X, HPE ProLiant DL580, and HPE Apollo 2000. Bridges is interconnected by Intel Omni-Path Architecture fabric, deployed in a custom topology for Bridges’ anticipated workloads.”

Video: Intel Forms Strategic Partnership with The Alan Turing Institute

In this video from SC15, Patrick Wolfe from the Alan Turing Institute and Karl Solchenbach from Intel describe a strategic partnership to deliver a research program focussed on HPC and data analytics. Created to promote the development and use of advanced mathematics, computer science, algorithms and big data for human benefit, the Alan Turing Institute is a joint venture between the universities of Warwick, Cambridge, Edinburgh, Oxford, UCL and EPSRC.

IBM Ramps Up Apache Spark at SC15

“What we’re previewing here today is a capability to have an overarching software, resource scheduler and workflow manager that takes all of these disparate sources and unifies them into a single view, making hundreds or thousands of computers look like one, and allowing you to run multiple instances of Spark. We have a very strong Spark multitenancy capability, so you can run multiple instances of Spark simultaneously, and you can run different versions of Spark, so you don’t obligate your organization to upgrade in lockstep.”

Video: General Atomics Delivers Data-Aware Cloud Storage Gateway with ArcaStream

“Ngenea’s blazingly-fast on-premises storage stores frequently accessed active data on the industry’s leading high performance file system, IBM Spectrum Scale (GPFS). Less frequently accessed data, including backup, archival data and data targeted to be shared globally, is directed to cloud storage based on predefined policies such as age, time of last access, frequency of access, project, subject, study or data source. Ngenea can direct data to specific cloud storage regions around the world to facilitate remote low latency data access and empower global collaboration.”

1degreenorth to Prototype HPDA Infrastructure in Singapore

At SC15, 1degreenorth announced plans to build an on-demand High Performance Computing Big DataAnalytics (“HPC-BDA”) infrastructure the National Supercomputing Center (NSCC) Singapore. The prototype will be used for experimentation and proof-of-concept projects by the big data and data science community in Singapore.

Call for Participation: HPC Advisory Council Stanford Conference

The HPC Advisory Council Stanford Conference 2016 has issued its Call for Participation. The event will take place Feb 24-25, 2016 on the Stanford University campus at the new Jen-Hsun Huang Engineering Center. “The HPC Advisory Council Stanford Conference 2016 will focus on High-Performance Computing usage models and benefits, the future of supercomputing, latest technology developments, best practices and advanced HPC topics. In addition, there will be a strong focus on new topics such as Machine Learning and Big Data. The conference is open to the public free of charge and will bring together system managers, researchers, developers, computational scientists and industry affiliates.”

Share Your Machine Learning Story to Inspire Others

Baidu’s Chief Scientist Andrew Ng has started a Social Media campaign for inspiring people to study Machine Learning. “Regardless of where you learned Machine Learning, if it has had an impact on you or your work, please share your story on Facebook or Twitter in a short written or video post. I will invite the people who shared the 5 most inspirational stories to join me in a conversation on Google Hangout about the future of machine learning.”