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Red Hat steps up to POWER9 for HPC

In this video from SC17 in Denver, Dan McGuan from Red Hat describes the company’s Multi-Architecture HPC capabilities with the Power9 architecture. “Red Hat and IBM have a long history of collaborating on Linux, going back more than 18 years. We laid the groundwork for supporting POWER9 processors several years ago and continue to collaborate with IBM to enable broader architecture support for IBM Power Systems across Red Hat’s portfolio.”

Call for Papers: International Workshop on Accelerators and Hybrid Exascale Systems

The eight annual  International Workshop on Accelerators and Hybrid Exascale Systems (AsHES) has issued its Call for Papers. Held in conjunction with the 32nd IEEE International Parallel and Distributed Processing Symposium, the AsHES Workshop takes place May 23 in Vancouver, Canada. “This workshop focuses on understanding the implications of accelerators and heterogeneous designs on the hardware systems, porting applications, performing compiler optimizations, and developing programming environments for current and emerging systems. It seeks to ground accelerator research through studies of application kernels or whole applications on such systems, as well as tools and libraries that improve the performance and productivity of applications on these systems.”

NVIDIA races to patch GPU Drivers for Spectre and Meltdown

A new security bulletin from NVIDIA reveals that its GPU drivers are not immune to the Spectre and Meltdown exploits that affect nearly every modern CPU. This is bad news for HPC, where the company’s Tesla GPUs are widely deployed to accelerate applications. “Most of the updates are available now, although Tesla and GRID users will have to wait until late January.”

How AI is Reshaping HPC

Karl Freund from Moor Insights gave this talk at SC17. “Researchers have begun putting Machine Learning to work solving problems that do not lend themselves well to traditional numerical analysis, or that require unaffordable computational capacity. This talk with discuss three primary approaches being used today, and will share some case studies that show significant promise of lower latency, improved accuracy, and lower cost.”

Steve Oberlin from NVIDIA Presents: HPC Exascale & AI

Steve Oberlin from NVIDIA gave this talk at SC17 in Denver. “HPC is a fundamental pillar of modern science. From predicting weather to discovering drugs to finding new energy sources, researchers use large computing systems to simulate and predict our world. AI extends traditional HPC by letting researchers analyze massive amounts of data faster and more effectively. It’s a transformational new tool for gaining insights where simulation alone cannot fully predict the real world.”

Adapting Deep Learning to New Data Using ORNL’s Titan Supercomputer

Travis Johnston from ORNL gave this talk at SC17. “Multi-node evolutionary neural networks for deep learning (MENNDL) is an evolutionary approach to performing this search. MENNDL is capable of evolving not only the numeric hyper-parameters, but is also capable of evolving the arrangement of layers within the network. The second approach is implemented using Apache Spark at scale on Titan. The technique we present is an improvement over hyper-parameter sweeps because we don’t require assumptions about independence of parameters and is more computationally feasible than grid-search.”

Visualization on GPU Accelerated Supercomputers

Peter Messmer from NVIDIA gave this talk at SC17. “This talk is a summary about the ongoing HPC visualization activities, as well as a description of the technologies behind the developer-zone shown in the booth.” Messmer is a principal software engineer in NVIDIA’s Developer Technology organization, working with clients to accelerate their scientific discovery process with GPUs.

Transforming Financial Services with AI Technologies

As the financial industry increasingly realizes the impact of faster analytical insights on overall business strategy, artificial intelligence techniques like machine learning are permeating nearly every industry. Download the new white paper from HPE and NVIDIA to learn how to transform financial services with AI technologies, as well as drive business value with NVIDIA GPU-accelerated deep learning. 

Converging HPC, Big Data, and AI at the Tokyo Institute of Technology

Satoshi Matsuoka from the Tokyo Institute of Technology gave this talk at the NVIDIA booth at SC17. “TSUBAME3 embodies various BYTES-oriented features to allow for HPC to BD/AI convergence at scale, including significant scalable horizontal bandwidth as well as support for deep memory hierarchy and capacity, along with high flops in low precision arithmetic for deep learning.”

Video: Dell EMC AI Vision & Strategy

Jay Boisseau from Dell EMC gave this talk at SC17 in Denver. “Across every industry, organizations are moving aggressively to adopt AI | ML | DL tools and frameworks to help them become more effective in leveraging data and analytics to power their key business and operational use cases. To help our clients exploit the business and operational benefits of AI | ML | DL, Dell EMC has created “Ready Bundles” that are designed to simplify the configuration, deployment and management of AI | ML | DL solutions.”