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Agenda Posted: Forum Teratec in France

The Forum Teratec in France has posted their speaker agenda. With over 1300 attendees, the event takes place June 11-12 in Palaiseau. “The Forum Teratec is the premier international meeting for all players in HPC, Simulation, Big Data and Machine Learning (AI). It is a unique place of exchange and sharing for professionals in the sector. Come and discover the innovations that will revolutionize practices in industry and in many other fields of activity.”

Video: High Performance Computing on the Google Cloud Platform

“High performance computing is all about scale and speed. And when you’re backed by Google Cloud’s powerful and flexible infrastructure, you can solve problems faster, reduce queue times for large batch workloads, and relieve compute resource limitations. In this session, we’ll discuss why GCP is a great platform to run high-performance computing workloads. We’ll present best practices, architectural patterns, and how PSO can help your journey. We’ll conclude by demo’ing the deployment of an autoscaling batch system in GCP.”

Video: The Human Side of AI

 In this video from the GPU Technology Conference, Dan Olds from OrionX discusses the human impact of AI with Greg Schmidt from HPE. The industry buzz about artificial intelligence and deep learning typically focuses on hardware, software, frameworks,  performance, and the lofty business plans that will be enabled by this new technology. What we don’t […]

Video: Advancing U.S. Weather Prediction Capabilities with Exascale HPC

Mark Govett from NOAA gave this talk at the GPU Technology Conference. “We’ll discuss the revolution in computing, modeling, data handling and software development that’s needed to advance U.S. weather-prediction capabilities in the exascale computing era. Creating prediction models to cloud-resolving 1 KM-resolution scales will require an estimated 1,000-10,000 times more computing power, but existing models can’t exploit exascale systems with millions of processors. We’ll examine how weather-prediction models must be rewritten to incorporate new scientific algorithms, improved software design, and use new technologies such as deep learning to speed model execution, data processing, and information processing.”

Scaling Deep Learning for Scientific Workloads on the #1 Summit Supercomputer

Jack Wells from ORNL gave this talk at the GPU Technology Conference. “HPC centers have been traditionally configured for simulation workloads, but deep learning has been increasingly applied alongside simulation on scientific datasets. These frameworks do not always fit well with job schedulers, large parallel file systems, and MPI backends. We’ll share benchmarks between native compiled versus containers on Power systems, like Summit, as well as best practices for deploying learning and models on HPC resources on scientific workflows.”

NVIDIA Powers New Lab for AI Radiology

Today NVIDIA and the American College of Radiology announced a collaboration to enable thousands of radiologists nationwide to create and use AI for diagnostic radiology in their own facilities, using their own data, to meet their own clinical needs. “NVIDIA builds platforms that democratize the use of AI and we purpose-built the Clara AI toolkit to give every radiologist the opportunity to develop AI tools that are customized to their patients and their clinical practice,” said Kimberly Powell, vice president of Healthcare at NVIDIA. “Our successful pilot with the ACR is the first of many that will make AI more accessible to the entire field of radiology.”

Video: ATOM Consortium to Accelerate AI in Drug Discovery with NVIDIA

The Public-private consortium ATOM has announced today that it is collaborating with NVIDIA to scale ATOM’s AI-driven drug discovery platform. “Scientists at ATOM have created a predictive model development pipeline that calls upon large datasets to build and test predictive machine learning models which consider pharmacokinetics, safety, developability, and efficacy. NVIDIA will provide additional resources that will enable this pipeline to be run at increased scale and speed.”

Video: Prepare for Production AI with the HPE AI Data Node

In this video from GTC 2019 in San Jose, Harvey Skinner, Distinguished Technologist, discusses the advent of production AI and how the HPE AI Data Node offers a building block for AI storage. “The HPE AI Data Node is a HPE reference configuration which offers a storage solution that provides both the capacity for data, as well as a performance tier that meets the throughput requirements of GPU servers. The HPE Apollo 4200 Gen10 density optimized data server provides the hardware platform for the WekaIO Matrix flash-optimized parallel file system, as well as the Scality RING object store.”

NVIDIA GPUs Speed Altair OptiStruct structural analysis up to 10x

Last week at GTC, Altair announced that it has achieved up to 10x speedups with the Altair OptiStruct structural analysis solver on NVIDIA GPU-accelerated system architecture — with no compromise in accuracy. This speed boost has the potential to significantly impact industries including automotive, aerospace, industrial equipment, and electronics that frequently need to run large, high-fidelity simulations. “This breakthrough represents a significant opportunity for our customers to increase productivity and improve ROI with a high level of accuracy, much faster than was previously possible,” said Uwe Schramm, Altair’s chief technology officer for solvers and optimization. “By running our solvers on NVIDIA GPUs, we achieved formidable results that will give users a big advantage.”

Video: DDN Accelerates Ai, Analytics, and Deep Learning at GTC

In this video from the 2019 GPU Technology Conference, James Coomer from DDN describes the company’s high-speed storage solutions for Ai, Machine Learning, and HPC. “This week at GTC, DDN is showcasing its high speed storage solutions, including its A³I architecture and new customer use cases in autonomous driving, life sciences, healthcare, retail, and financial services. DDN next generation of A³I reference architectures include NVIDIA’s DGX POD, DGX-2, and the DDN’s AI400 parallel storage appliance.”