In this Nvidia podcast, Bryan Catanzaro from Baidu describes how machines with Deep Learning capabilities are now better at recognizing objects in images than humans. “AI gets better and better until it kind of disappears into the background,” says Catanzaro — NVIDIA’s head of applied deep learning research — in conversation with host Michael Copeland on this week’s edition of the new AI Podcast. “Once you stop noticing that it’s there because it works so well — that’s when it’s really landed.”
Today Cray announced the results of a deep learning collaboration with Microsoft CSCS designed to expand the horizons of running deep learning algorithms at scale using the power of Cray supercomputers. “Cray’s proficiency in performance analysis and profiling, combined with the unique architecture of the XC systems, allowed us to bring deep learning problems to our Piz Daint system and scale them in a way that nobody else has,” said Prof. Dr. Thomas C. Schulthess, director of the Swiss National Supercomputing Centre (CSCS). “What is most exciting is that our researchers and scientists will now be able to use our existing Cray XC supercomputer to take on a new class of deep learning problems that were previously infeasible.”
In this video from SC16, Roy Kim from Nvidia describes how the company is bringing in a new age of AI with accelerated computing for Deep Learning applications. “Deep learning is the fastest-growing field in artificial intelligence, helping computers make sense of infinite amounts of data in the form of images, sound, and text. Using multiple levels of neural networks, computers now have the capacity to see, learn, and react to complex situations as well or better than humans. This is leading to a profoundly different way of thinking about your data, your technology, and the products and services you deliver.”
“With up to eight high performance NVIDIA GPUs designed for maximum transfer bandwidth, the HPE Apollo 6500 is purpose-built for HPC and deep learning applications. Its high ratio of GPUs to CPUs, dense 4U form factor and efficient design enable organizations to run deep learning recommendation algorithms faster and more efficiently, significantly reducing model training time and accelerating the delivery of real-time results, all while controlling costs.”
In this podcast, the Radio Free HPC team reviews the results from SC16 Student Cluster Competition. “This year, the advent of clusters with the new Nvidia Tesla P100 GPUs made a huge impact, nearly tripling the Linpack record for the competition. For the first-time ever, the team that won top honors also won the award for achieving highest performance for the Linpack benchmark application. The team “SwanGeese” is from the University of Science and Technology of China. In traditional Chinese culture, the rare Swan Goose stands for teamwork, perseverance and bravery.”
“With demand for graduates with AI skills booming, we’ve released the NVIDIA Deep Learning Teaching Kit to help educators give their students hands on experience with GPU-accelerated computing. The kit — co-developed with deep-learning pioneer Yann LeCun, and largely based on his deep learning course at New York University — was announced Monday at the NIPS machine learning conference in Barcelona. Thanks to the rapid development of NVIDIA GPUs, training deep neural networks is more efficient than ever in terms of both time and resource cost. The result is an AI boom that has given machines the ability to perceive — and understand — the world around us in ways that mimic, and even surpass, our own.”
Accelerated computing continues to gain momentum as the HPC community moves towards Exascale. Our recent Tesla P100 GPU review shows how these accelerators are opening up new worlds of performance vs. traditional CPU-based systems and even vs. NVIDIA’s previous K80 GPU product. We’ve got benchmarks, case studies, and more in the insideHPC Research Report on GPU Accelerators.
Today the Barcelona Supercomputing Center announced plans to MareNostrum 4, a 13.7 Petaflop supercomputer that will be 12.4 times more powerful than the current MareNostrum 3 system. In a contract valued at almost €30 million, IBM will integrate in one sole machine using its own technologies alongside those of Lenovo, Intel, and Fujitsu.
“Most of the IT innovation that is happening today is with a cloud-first model,” said Joris Poort, co-founder and CEO of Rescale. “We’re building a platform that can satisfy and accelerate the ideas of the world’s top scientists and thinkers. From automotive design to drug discovery and even actual rocket science, we’re empowering our customers as leaders in their respective fields, to accomplish more and innovation faster.”