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Penguin Computing to share AI Best Practices at GPU Technology Conference

Today Penguin Computing announced that Director of Advanced Solutions, Kevin Tubbs, Ph.D., will be speaking at NVIDIA’s GPU Technology Conference (GTC) on best practices in artificial intelligence. “On the second day of the conference, Tubbs will lead the “Best Practices in Designing and Deploying End-to-End HPC and AI Solutions” session. The focus of the session will be challenges faced by organizations looking to build AI systems and the design principles and technologies that have proven successful in Penguin Computing AI deployments for customers in the Top 500.”

HPE Launches Vertical AI Solutions

Today Hewlett Packard Enterprise announced new offerings to help customers ramp up, optimize and scale artificial intelligence usage across business functions to drive outcomes such as better demand forecasting, improved operational efficiency and increased sales. “HPE is best positioned to help customers make AI work for their enterprise, regardless of where they are in their AI adoption. While others provide AI components, we provide complete AI solutions from strategic advisory to purpose-built technology, operational support and a strong AI partner ecosystem to tailor the right AI solution for each organization.”

Video: IBM Quantum Computing will be “Mainstream in Five Years”

Talia Gershon from the Thomas J. Watson Research Center gave this talk at the 2018 IBM Think conference. “There is a whole class of problems that are too difficult for even the largest and most powerful computers that exist today to solve. These exponential challenges include everything from simulating the complex interactions of atoms and molecules to optimizing supply chains. But quantum computers could enable us to solve these problems, unleashing untold opportunities for business.”

IBM Launches Deep Learning as a Service

“IBM’s goal is to make it easier for you to build your deep learning models. Deep Learning as a Service has unique features, such as Neural Network Modeler, to lower the barrier to entry for all users, not just a few experts. The enhancements live within Watson Studio, our cloud-native, end-to-end environment for data scientists, developers, business analysts and SMEs to build and train AI models that work with structured, semi-structured and unstructured data — while maintaining an organization’s existing policy/access rules around the data.”

Optalysys Speeds Deep Learning with Optical Processing

“Optalysys has for the first time ever, applied optical processing to the highly complex and computationally demanding area of CNNs with initial accuracy rates of over 70%. Through our uniquely scalable and highly efficient optical approach, we are developing models that will offer whole new levels of capability, not only cloud-based but also opening up the extraordinary potential of CNNs to mobile systems.”

What a 200G HDR InfiniBand Solution Means for Today’s Advanced Data Centers

The world of today’s HPC computing is driven by the ever-increasing generation and consumption of digital information. And the ability to analyze this rapidly growing pool of data, and extrapolate meaningful insights, gives modern businesses a competitive edge. Download the full report, “Introducing 200G HDR InfiniBand Solutions,” to learn about how Mellanox Technologies end-to-end 200G HDR InfiniBand solution is helping enable the next generation of data centers.

Intel MKL Speeds Up Automated Driving Workloads on the Intel Xeon Processor

The automated driving developer community typically uses Eigen*, a C++ math library, for the matrix operations required by the Extended Kalman Filter algorithm. EKF usually involves many small matrices. However most HPC library routines for matrix operations are optimized for large matrices. “Intel MKL provides highly-tuned xGEMM function for matrix-matrix multiplication, with special paths for small matrices. Eigen can take advantage of Intel MKL through use of a compiler flag. A significant speedup results when using Eigen and Intel MKL and compiling the automated driving apps with the latest Intel C++ compiler.”

Google Goes for Quantum Supremacy with 72-Qbit Bristlecone Chip

Over at the Google Research Blog, Julian Kelly writes that the company has developed a new 72-Qbit quantum processor called Bristlecone. “We are cautiously optimistic that quantum supremacy can be achieved with Bristlecone, and feel that learning to build and operate devices at this level of performance is an exciting challenge!”

Deploy Serverless TensorFlow Models using Kubernetes, OpenFaaS, GPUs and PipelineAI

Chris Fregly from PipelineAI gave this talk at the Stanford HPC Conference. “Applying my Netflix experience to a real-world problem in the ML and AI world, I will demonstrate a full-featured, open-source, end-to-end TensorFlow Model Training and Deployment System using the latest advancements with TensorFlow, Kubernetes, OpenFaaS, GPUs, and PipelineAI.”

GPU Technology Conference Returns to San Jose March 26-29

NVIDIA will host thousands of the world’s leading AI experts at its ninth annual GPU Technology Conference (GTC) on March 26-29 in San Jose, California. “GTC is where the world’s leading researchers and business leaders learn how to harness the power of AI,” said Greg Estes, vice president of Developer Programs at NVIDIA. “As GPU computing continues to drive the AI revolution, GTC is where you’ll see the future take shape.”