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HPC Top 5 Stories: Dec 1, 2017

Check out weekly insights into the world of HPC and AI with this HPC Top 5 Stories.

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HPC Top 5 Stories: Dec 1, 2017

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  1. HPC TOP 5 STORIES Weekly Insights into the World of High Performance Computing

  2. HPC AND AI HAVE PAVED THE WAY FOR GROUNDBREAKING DISCOVERIES IN SCIENCE, MEDICINE, AND OTHER FIELDS…

  3. PROVING THAT AI IS THE FUTURE OF SUPERCOMPUTING…

  4. TOP 5 HERE ARE THE “TOP FIVE’ STORIES HIGHLIGHTING WHAT’S HOT IN HPC AND AI

  5. TOP 5 1. NVIDIA and GE Partner to Bring AI-Assisted Data Analytics and Visualization to Healthcare 2. Mainstreaming HPC Codes will Propel the Next GPU Wave 3. Malware Detection in Executables Using Neural Networks 4. For HPC and Deep Learning, GPUs are here to stay 5. Bonsai Achieves AWS Machine Learning Competency Status

  6. 1 NVIDIA AND GE PARTNER TO BRING AI-ASSISTED DATA ANALYTICS AND VISUALIZATION TO HEALTHCARE Artificial Intelligence and machine learning might be all the buzz when it comes to emerging technologies like self-driving cars and smart assistants, like Cortana or Siri. However, there's no more valuable a use for machine learning and AI, than in the healthcare field, where the average hospital generates some 50 petabytes of data annually but only a very small percentage of it is able to be analyzed fully or acted upon. And when it comes to healthcare, that can literally be the difference between saving a life or losing one. NVIDIA has carved out a large percentage of the AI accelerator market with its powerful Tesla GPUs in a variety of applications, beyond just machine vision for self driving cars. Data center deployments for deep learning GPUs are NVIDIA's stranglehold currently, where Tesla enables a myriad of industrial applications that harness the power of AI in the cloud. FORBES ARTICLE

  7. 2 MAINSTREAMING HPC CODES WILL PROPEL THE NEXT GPU WAVE While HPC applications have been around for a long time, no one would ever call HPC easy. And if simulation and modeling of all kinds, augmented by machine learning, is to get easier, then it is going to have to get easier to install, update, and manage traditional HPC and new AI applications. To that end, NVIDIA, which has the most at stake in the GPU revolution that is sweeping both HPC and AI, is investing heavily in making it easier to deploy these applications. NEXT PLATFORM ARTICLE LEARN MORE LEARN MORE

  8. 3 MALWARE DETECTION IN EXECUTABLES USING NEURAL NETWORKS The need to develop techniques that can adapt to the rapidly changing malware ecosystem is seemingly a perfect fit for machine learning. Indeed, a number of startups and established cyber-security companies have started building machine learning based systems. These companies typically spend considerable effort in feature engineering and analysis to build high quality systems. But what if we could build an anti-virus system without any feature engineering? That could allow the same system to detect malware across a variety of operating systems and hardware. We demonstrate a significant step towards this goal in our most recent research paper. BLOG

  9. 4 FOR HPC AND DEEP LEARNING, GPUS ARE HERE TO STAY There was an interesting story published earlier this week in which NVIDIA’s founder and CEO, Jensen Huang, said: ‘As advanced parallel-instruction architectures for CPU can be barely worked out by designers, GPUs will soon replace CPUs’. There are only so many processing cores you can fit on a single CPU chip. There are optimized applications that take advantage of a number of cores, but typically they are used for sequential serial processing (although Intel is doing an excellent job of adding more and more cores to its CPUs and getting developers to program multicore systems). By contrast, a GPU has massively parallel architecture consisting of many thousands of smaller, more efficient cores designed for handling multiple tasks simultaneously. INSIDEHPC ARTICLE

  10. 5 BONSAI ACHIEVES AWS MACHINE LEARNING COMPETENCY STATUS Bonsai, provider of an AI solution that empowers enterprises to build intelligent systems, announced today that it has achieved Amazon Web Services (AWS) Machine Learning (ML) Competency status. This designation recognizes Bonsai for enabling developers, machine learning practitioners, and subject matter experts with tools to train deep reinforcement learning models and enable predictive capabilities within customer applications. Achieving the AWS ML Competency differentiates Bonsai as an AWS Partner Network (APN) member that has built solutions that help organizations enhance industrial applications with machine intelligence. Attaining the AWS ML Competency demonstrates to our customers that Bonsai has validated ML expertise on AWS. BONSAI BLOG

  11. HOW CAN HPC IMPACT YOUR BUSINESS? LEARN MORE

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