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NVIDIA Offers Framework to Solve AI System Challenges

At the recent NVIDIA GPU Technology Conference (GTC) 2018, Jensen Huang, NVIDIA President and CEO, during his presentation focused on a new framework designed to contextualize the key challenges using AI systems and delivering deep learning-based solutions. A new white paper sponsored by NVIDIA outlines these requirements — coined PLASTER.

See How the Convergence of HPC and AI is Changing Supercomputing at ISC 2018

It’s a fascinating time for High Performance Computing. The convergence of AI, analytics, and simulation and modeling is transforming systems and users. “So, there’s a lot to talk about it at ISC 2018, including announcements from Intel on next-generation Intel® Omni-Path Architecture and Intel® Select Solutions for Professional Visualization, to Machine Learning Day with Pradeep Dubey, and demos, presentations, and panel discussions in Intel’s Collaboration Hub.”

New eGuide: Practical Considerations for Embracing AI in Your HPC Environment

The advent of AI is creating new possibilities to tackle increasingly complex research beyond the traditional HPC analytics, modeling, and simulation workloads. This guest post from Intel highlights key points from its new eGuide that focuses on embracing AI in your HPC environment. “Thanks to the efforts of HPC experts and those they support, we face a bright and exciting future of scientific understanding and innovation to benefit humanity.”

AI Hardware to Support the Artificial Intelligence Software Ecosystem

Balance ratios are key to understanding the plethora of AI hardware solutions that are being developed or are soon to become available. This post from an insideHPC Special Report explores AI hardware options to support the growing artificial intelligence software ecosystem. 

AI Software: Understanding the Rapidly Expanding Ecosystem

The hardware and software for AI devices is rapidly evolving, so it is important to procure wisely for the future without incurring technology or vendor lock in. This post from an insideHPC Special Report focuses on AI software and how to best use and understand this rapidly expanding ecosystem. 

AI Systems Designed to Learn in a Limited Information Environment

In a special report, Intel offers details on use cases that explore AI systems and those designed to learn in a limited information environment. “AI systems that can compete against and beat humans in limited information games have great potential, because so many activities between humans happen in the context of limited information such as financial trading and negotiations and even the much simpler task of buying a home.”

AI Technology: The Answer to Diffusion Compartment Imaging Challenges

Use cases show AI technology, like what’s used in an optimized Diffusion Compartment Imaging (DCI) technique, is growing the potential of HPC computing. AI is thought to be a solution to many of DCI’s challenges. “A complete Diffusion Compartment Imaging study can now be completed in 16 minutes on a workstation, which means Diffusion Compartment Imaging can now be used in emergency situations, in a clinical setting, and to evaluate the efficacy of treatment. Even better, higher resolution images can be produced because the optimized code scales.”

AI and HPC: Inferencing, Platforms & Infrastructure

The popularity of “better than human” classification on tasks that people do well (such as recognizing faces, Internet image search, self-driving cars, etcetera) has reached a mass audience. “What has been lacking is coverage that machine learning is also fantastic at performing tasks that humans tend to do poorly.”

Video: HPE Showcases Innovation for HPC at SC17

In this video, Bill Mannel gives a booth tour that highlights some of the amazing HPC innovations on display in the HPE booth at SC17. “HPE’s first ARM-based HPC system brings more choice and flexibility to HPC customers. The Apollo 70, using Cavium’s 64-bit ARMv8-A ThunderX2 Server Processor, is purpose-built for memory intensive HPC workloads and delivers up to 33 percent more memory bandwidth than today’s industry standard servers.”

An Overview of AI in the HPC Landscape

The demand for performant and scalable AI solutions has stimulated a convergence of science, algorithm development, and affordable technologies to create a software ecosystem designed to support the data scientist. “It is very important to understand that time-to-model and the accuracy of the resulting model are really the only performance metrics that matter when training because the goal is to quickly develop a model that represents the training data with high accuracy.”