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Video: ZFS Improvements for Lustre

In this video from LAD’17 in Paris, Adreas Dilger from Intel presents: ZFS Improvements for Lustre. “Lustre is the Parallel file system of choice for High Performance Computing and large file applications. To meet the capacity and throughput requirements of HPC workloads, Lustre has traditionally required adoption of custom proprietary storage products leading to vendor lock-in and reduced innovation. The evolution of software defined high availability platforms like ZFS running on Linux now make it possible to meet the performance requirements of HPC on open industry standard x86 platforms.”

Intel Select Solutions for HPC Debut at SC17

Intel Select Solutions HPC provide a fast path for purchasing and deploying a cluster for simulation and modeling workloads with a pre-validated selection of components designed to meet the demands of HPC applications and workflows. These systems provide the capabilities and agility needed to support a range of different workloads and reduce or eliminate the need for multiple single-purpose systems. In addition, the performance of key system characteristics are verified for Intel Select Solutions for Simulation and Modeling at both the node and cluster level.

Lenovo Steps up with Intel Select Solutions for HPC

In this video, Trish Damkroger from Intel and Madhu Matta from Lenovo describe how Intel Select Solutions for HPC make it easy to scale application performance. “Intel Select Solutions HPC provide a fast path for purchasing and deploying a cluster for simulation and modeling workloads with a pre-validated selection of components designed to meet the demands of HPC applications and workflows.”

Catch Today’s ‘Artificial Intelligence and The Virtuous Cycle of Compute’ Presentation by Intel

At SC17, Intel is reinforcing its ongoing commitment to HPC and AI technologies. If you want to learn more about Intel’s investment in Artificial Intelligence, and the convergence with HPC, then be sure to catch the future-focused presentation on “Artificial Intelligence and The Virtuous Cycle of Compute” by Pradeep Dubey, Intel Fellow, and Director of Parallel Computing Lab.  

SC17 Preview: Artificial Intelligence and The Virtuous Cycle of Compute

In this video, Pradeep Dubey from Intel Labs describes his upcoming SC17 Invited Talk on Artificial Intelligence. “Dubey will discuss how the convergence of AI, Big Data, HPC systems, and algorithmic advances are transforming the relationship between computers and humans, disrupting past notions of a partnership where humans made all the “intelligent” decisions.”

Intel and the Coming AI Revolution

In this video from the Intel HPC Developer Conference, Gadi Singer from Intel describes how the company is moving forward with Artificial Intelligence. “We are deeply committed to unlocking the promise of AI: conducting research on neuromorphic computing, exploring new architectures and learning paradigms.”

Video: Applying AI to Science

In this video from the Intel HPC Developer Conference, Prabhat from NERSC describes how AI applies to science. “Looking ahead, Prabhat sees broad applications for deep learning in scientific research beyond climate science—especially in astronomy, cosmology, neuroscience, material science, and physics.”

Intel at SC17: Showcasing HPC technologies, luminary speakers, and a virtual motorsports experience

This year at SC17, Intel offers many opportunities to learn about the newest technologies, emerging fields like Artificial Intelligence, and the ways organizations are applying those capabilities for real-world applications.”

Register Now For the Intel HPC Developer Conference 2017

Powerful technologies today fuel tomorrow’s HPC and High-Performance Data Analytics innovations and help organizations accelerate toward discoveries. Get ahead of the curve at the Intel HPC Developer Conference 2017 in Denver, Colorado on November 11-12.

1000x Faster Deep-Learning at Petascale Using Intel Xeon Phi Processors

A cumulative effort over several years to scale the training of deep-learning neural networks has resulted in the first demonstration of petascale deep-learning training performance, and further to deliver this performance when solving real science problems. The result reflects the combined efforts of NERSC (National Energy Research Scientific Computing Center), Stanford and Intel to solve real world use cases rather than simply report on performance benchmarks.