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Speed Machine Learning with the Model Zoo for Intel Architecture

Intel has launched a Model Zoo for Intel Architecture, an open-sourced collection of optimized machine learning inference applications that demonstrates how to get the best performance on Intel platforms. The project contains more than 20 pre-trained models, benchmarking scripts, best practice documents, and step-by-step tutorials for running deep learning (DL) models optimized for Intel Xeon Scalable processors.

Red Hat Teams with NVIDIA to Accelerate Machine Learning in the Cloud

Today Red Hat announced it has deepened its alliance with NVIDIA to accelerate the enterprise adoption of AI, machine learning and data analytics workloads in production environments. To move thins along, Red Hat is launching an early access program for prospective customers. “High-performance technologies are moving at a brisk rate into enterprise data centers to accelerate product development and business operations – including financial services, ERP and sales analysis, fraud detection and cybersecurity, and machine learning-AI,” said Steve Conway, senior vice president of research, Hyperion Research. “The hybrid cloud solutions from Red Hat and NVIDIA are designed to make accelerated computing use easier for enterprises on-premise and in the cloud.”

Cray Powers Weather Forecasting at ZAMG in Austria

Today Cray announced that the Central Institution for Meteorology and Geodynamics in Austria (ZAMG) is using a Cray supercomputer to support a multi-year weather nowcasting project with the University of Vienna to benefit society and industry. “Using deep learning methods, ZAMG is leveraging its Cray CS-Storm supercomputer to optimize the orientation of wind-powered generators for maximum efficiency and to train neural networks with current and historical weather data.”

SC19 Posts Workshop Schedule

“These topical workshops are bringing together hardware and software trends spanning various subjects including data analysis, visualization, machine learning for HPC, deep learning, performance benchmarking, parallel computing, correctness, computational reproducibility along with education for HPC. This broader set of topics is just another testimony of how SC19 is reaching out and including new communities.”

Google Cloud TPU Pods Speed Machine Learning

Today Google announced that its Google Cloud TPU Pods are now publicly available in beta. Designed to help Machine Learning researchers iterate faster and train more capable machine learning models, TPU Pods can include more than 1,000 individual TPU chips connected by an ultra-fast, two-dimensional toroidal mesh network.

Hyperion Research to host HPC Market Update Breakfast at ISC 2019

Hyperion Research will hold their annual HPC Market Update briefing at ISC 2019 in Frankfurt. “As Hyperion Research, we continue all the worldwide activities that spawned the world’s most respected HPC industry analyst group. For more than 25 years, we’ve helped IT professionals, business executives, and the investment community make fact-based decisions on technology purchases and business strategy.”

ExaLearn: The ECP Co-Design Center for Machine Learning

In this video from the HPC User Forum, Frank Alexander from Brookhaven National Laboratory presents: ExaLearn – ECP Co-Design Center for Machine Learning. “It is increasingly clear that advances in learning technologies have profound societal implications and that continued U.S. economic leadership requires a focused effort, both to increase the performance of those technologies and to expand their applications. Linking exascale computing and learning technologies represents a timely opportunity to address those goals.”

Excelero Powers AI as a Service with Shared NVMe at InstaDeep

“InstaDeep offers a pioneering AI as a Service solution enabling organizations of any size to leverage the benefits of AI and Machine Learning without the time, costs and expertise required to run their own AI stacks. Excelero’s NVMesh, in turn, allows InstaDeep to access the low-latency, high-bandwidth performance that is essential for running customer AI and ML workloads efficiently – and gain the scalability vital to InstaDeep’s own rapid growth.”

OSS rolls out GPUltima Rugged Rack-Scale AI Solution

Today One Stop Systems announced plans to demonstrate its award winning AI on the Fly system platforms at the Sea-Air-Space 2019 conference in Maryland. The company’s AI-system platforms accelerate autonomous vehicles, record high-speed surveillance data, detect real-time threats, deploy countermeasures and sift through mountains of radio transmission data to keep the warfighter at the forefront of AI technology.

‘AI on the Fly’: Moving AI Compute and Storage to the Data Source

The impact of AI is just starting to be realized across a broad spectrum of industries. Tim Miller, Vice President Strategic Development at One Stop Systems (OSS), highlights a new approach — ‘AI on the Fly’ — where specialized high-performance accelerated computing resources for deep learning training move to the field near the data source. Moving AI computation to the data is another important step in realizing the full potential of AI.