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Video: Introduction to OpenACC

Vasileios Karakasis from CSCS gave this talk at the the Directive Based GPU Programming Workshop. “Directives-based programming facilitates the task of parallelizing your application by letting you focus on its parallel logic rather than on the very details and the low-level intricacies of the GPU architecture. In this course, we will introduce the OpenACC programming paradigms for the GPU. We will cover the parallel execution model and how it can be used to leverage parallelism, the memory model and how this differs from the classic CPU paradigm.”

Video: NVIDIA Announces Turing GPUs and CUDA Toolkit 10

Today at SIGGRPAH, NVIDIA announced its newest GPUs based on the new Turing architecture. ”
This fundamentally changes how computer graphics will be done, it’s a step change in realism,” Huang told an audience of more than 1,200 graphics pros gathered at the sleek glass and steel Vancouver Convention Center, which sits across a waterway criss-crossed by cruise ships and seaplanes from the stunning North Shore mountains.

One Stop Systems rolls out Magma ExpressBox eGPU with Thunderbolt 3

Today One Stop Systems introduced the Magma ExpressBox 3T-V3-eGPU, a new external graphics card solution with Thunderbolt 3. The ExpressBox 3T-V3-eGPU can transform both computers and laptops with Thunderbolt 3 connections into powerful workstations. “We’re committed to providing mobile professionals with the latest technologies for performing AI, CAE and rendering applications,” said Steve Cooper, CEO of OSS. “Our new ExpressBox 3T-V3-eGPU, like all of our Magma ExpressBox expansion products, enables professionals to remain mobile without sacrificing office workstation performance, but now takes it to a whole new level with NVIDIA technology.”

Training Generative Adversarial Models over Distributed Computing Systems

Gul Rukh Khattak from CERN gave this talk at PASC18. “We use a dataset composed of the energy deposition from electron, photons, charged and neutral hadrons in a fine grained digital calorimeter. The training of these models is quite computing intensive, even with the help of GPGPU, and we propose a method to train them over multiple nodes and GPGPU using a standard message passing interface. We report on the scalings of time-to-solution.”

Fast.AI Achieves Record ImageNet performance with NVIDIA V100 Tensor Core GPUs

The NVIDIA blog points us to this story on how Fast.ai just completed a new deep learning benchmark milestone. Using NVIDIA V100 GPUs on AWS with PyTorch, the company now has the ability to train ImageNet to 93% accuracy in just 18 minutes. “DIU and fast.ai will be releasing software to allow anyone to easily train and monitor their own distributed models on AWS, using the best practices developed in this project,” said Jeremy Howard, a founding researcher at fast.ai. “We entered this competition because we wanted to show that you don’t have to have huge resources to be at the cutting edge of AI research, and we were quite successful in doing so.”

Dell EMC Powers High Performance Computing at HPC Wales

In this video from ISC 2018, Biagio Lucini from Swansea University describes how Dell EMC is working with Supercomputing Wales on advanced computing projects including the Bloodhound Supersonic car. “Bloodhound is a global Engineering Adventure, using a 1,000mph World Land Speed Record attempt to inspire the next generation to enjoy, explore and get involved in science, technology, engineering and mathematics.”

Dell EMC Accelerates Artificial Intelligence Adoption for Digital Transformation

Today Dell EMC announced new Ready Solutions for AI. With specialized designs for Machine Learning with Hadoop and Deep Learning with NVIDIA, the Dell EMC Ready Solutions simplify AI environments, deliver faster, deeper insights than the competition1, and leverage Dell EMC’s proven expertise to help organizations realize the full potential of AI. “What we’re announcing today allows customers at any scale to start seeing better business outcomes and positions them for AI’s increasingly important role in the future.”

SC18 Preview: Bryan Catanzaro on “Applying Deep Learning”

SC18 is starting their series of Invited Talk Previews this week with AI luminary Bryan Catanzaro. Now at NVIDIA, Catanzaro is one of the most respected (and entertaining) speakers in the field of Machine Learning. “I will discuss how we go about applying deep learning to our work at NVIDIA, solving problems in a variety of domains from graphics and vision to text and speech. I’ll discuss the properties of successful machine learning applications, the criteria that we use to choose projects, and things to watch out for while creating new deep learning applications. I’ll discuss the role of HPC in helping us conduct our research, and I’ll show some examples of projects that benefit from scale.”

Dell EMC Gains Momentum on HPC & AI at ISC 2018

In this video from ISC 2018, Thierry Pelligrino from Dell EMC describes how the company is moving forward with HPC and AI solutions for customers in science, engineering, and the Enterprise. “HPC is great practice. AI is the buzzword. But the two need to come together. You can’t really get value out of your data if you don’t know how to use the highest performing computing cycles. You also need to think about how you use the data in storage and how you make it move around with a lot of networking gear.”

Podcast: Bill Dally from NVIDIA on What’s Next for AI

“NVIDIA researchers are gearing up to present 19 accepted papers and posters, seven of them during speaking sessions, at the annual Computer Vision and Pattern Recognition conference next week in Salt Lake City, Utah. Joining us to discuss some of what’s being presented at CVPR, and to share his perspective on the world of deep learning and AI in general is one of the pillars of the computer science world, Bill Dally, chief scientist at NVIDIA.”