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NASA Perspectives on Deep Learning

Nikunj Oza from NASA Ames gave this talk at the HPC User Forum. “This talk will give a broad overview of work at NASA in the space of data sciences, data mining, machine learning, and related areas at NASA. This will include work within the Data Sciences Group at NASA Ames, together with other groups at NASA and university and industry partners. We will delineate our thoughts on the roles of NASA, academia, and industry in advancing machine learning to help with NASA problems.”

GPUs Accelerate Population Distribution Mapping Around the Globe

With the Earth’s population at 7 billion and growing, understanding population distribution is essential to meeting societal needs for infrastructure, resources and vital services. This article highlights how NVIDIA GPU-powered AI is accelerating mapping and analysis of population distribution around the globe. “If there is a disaster anywhere in the world,” said Bhaduri, “as soon as we have imaging we can create very useful information for responders, empowering recovery in a matter of hours rather than days.”

The AI Revolution: Unleashing Broad and Deep Innovation

For the AI revolution to move into the mainstream, cost and complexity must be reduced, so smaller organizations can afford to develop, train and deploy powerful deep learning applications. It’s a tough challenge. The following guest article from Intel explores how businesses can optimize AI applications and integrate them with their traditional workloads. 

CCIX Project to link ARM Processors and FPGAs for HPC

Today ARM, Xilinx, Cadence, and Taiwan Semiconductor announced plans to produce the first test chip for the Cache Coherent Interconnect for Accelerators (CCIX) project. CCIX (pronounced “C6”) aims to prove that many-core ARM processors linked to FPGAs have a home in HPC. “The test chip will not only demonstrate how the latest Arm technology with coherent multichip accelerators can scale across the data center, but reinforces our commitment to solving the challenge of accessing data quickly and easily.”

Video: Characterization and Benchmarking of Deep Learning

 Natalia Vassilieva from HP Labs gave this talk at the HPC User Forum in Milwaukee. “Our Deep Learning Cookbook is based on a massive collection of performance results for various deep learning workloads on different hardware/software stacks, and analytical performance models. This combination enables us to estimate the performance of a given workload and to recommend an optimal hardware/software stack for that workload. Additionally, we use the Cookbook to detect bottlenecks in existing hardware and to guide the design of future systems for artificial intelligence and deep learning.”

New OrionX Survey: Insights in Artificial Intelligence

In this Radio Free HPC podcast, Dan Olds and Shahin Khan from OrionX describe their new AI Survey. “OrionX Research has completed one the most comprehensive surveys to date of Artificial Intelligence, Machine Learning, and Deep Learning. With over 300 respondents in North America, representing 13 industries, our model indicates a confidence level of 95% and a margin of error of 6%. Covering 144 questions/data points, it provides a comprehensive view of what customers are doing and planning to do with AI/ML/DL.”

Call for Participation: GTC 2018 in San Jose

The GPU Technology Conference (GTC 2018) has issued their Call for Participation. The event takes place March 26-29 in San Jose, California. “Don’t miss this unique opportunity to participate in the world’s most important GPU event, NVIDIA’s GPU Technology Conference (GTC 2018). Sign up to present a talk, poster, or lab on how GPUs power the most dynamic areas in computing today—including AI and deep learning, big data analytics, healthcare, smart cities, IoT, HPC, VR, and more.”

Trends in the Worldwide HPC Market

In this video from the HPC User Forum in Milwaukee, Earl Joseph and Steve Conway from Hyperion Research present and update on HPC, AI, and Storage markets. “Hyperion Research forecasts that the worldwide HPC server-based AI market will expand at a 29.5% CAGR to reach more than $1.26 billion in 2021, up more than three-fold from $346 million in 2016.”

NVIDIA Volta GPUs to Help CDDS Advance Medicine with AI

Over at the NVIDIA Blog, Abdul Hamid Halabi writes that the Center for Clinical Data Science (CCDS) today received the world’s first NVIDIA DGX systems with Volta. “Soon, Boston-area radiologists will have AI “assistants” integrated into their daily workflows, helping them more quickly and accurately diagnose disease from MRIs, CAT scans, X-rays and more. The trained neural networks residing on DGX-1 systems in CCDS’s data center are in a constant state of learning, continually ingesting countless medical images worldwide.”

The Intel Scalable System Framework: Kick-Starting the AI Revolution

Like many other HPC workloads, deep learning is a tightly coupled application that alternates between compute-intensive number-crunching and high-volume data sharing. Intel explores how the Intel Scalable System can act as a solution for a high performance computing platform that can run deep learning workloads and more.