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Podcast: Astronomers Turn to AI as New Telescopes Come Online

In this AI Podcast, Brant Robertson from UC Santa Cruz describes how astronomers are turning to AI to turn the vast quantities of data that will be pouring out of next-generation telescopes into world-changing scientific discoveries. “Good news: astronomers are getting new tools to let them see further, better than ever before. The bad news: they’ll soon be getting more data than humans can handle.”

Achieving ExaOps with the CoMet Comparative Genomics Application

Wayne Joubert’s talk at the HPC User Forum described how researchers at the US Department of Energy’s Oak Ridge National Laboratory (ORNL) achieved a record throughput of 1.88 ExaOps on the CoMet algorithm. As the first science application to run at the exascale level, CoMet achieved this remarkable speed analyzing genomic data on the recently launched Summit supercomputer.

Video: Can FPGAs compete with GPUs?

John Romein from ASTRON gave this talk at the GPU Technology Conference. “We’ll discuss how FPGAs are changing as a result of new technology such as the Open CL high-level programming language, hard floating-point units, and tight integration with CPU cores. Traditionally energy-efficient FPGAs were considered notoriously difficult to program and unsuitable for complex HPC applications. We’ll compare the latest FPGAs to GPUs, examining the architecture, programming models, programming effort, performance, and energy efficiency by considering some real applications.”

NVIDIA DGX-2 Delivers Record Performance on STAC-A3 Benchmark

Today NVIDIA announced record performance on STAC-A3, the financial services industry benchmark suite for backtesting trading algorithms to determine how strategies would have performed on historical data. “Using an NVIDIA DGX-2 system running accelerated Python libraries, NVIDIA shattered several previous STAC-A3 benchmark results, in one case running 20 million simulations on a basket of 50 instruments in the prescribed 60-minute test period versus the previous record of 3,200 simulations.”

NVIDIA Builds First AI Platform for NHS Hospitals in the U.K.

Today NVIDIA and King’s College London announced they are partnering to build an AI platform designed to allow specialists in the U.K.’s National Health Service to train computers to automate the most time-consuming part of radiology interpretation. “The NVIDIA DGX-2 AI system’s large memory and massive computing power make it possible for us to tackle training of large, 3D datasets in minutes instead of days while keeping the data secure on the premises of the hospital.”

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.”

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.”

AMD to Power Exascale Cray System at ORNL

Today AMD announced a new exascale-class supercomputer to be delivered to ORNL in 2021. Built by Cray, the “Frontier” system is expected to deliver more than 1.5 exaFLOPS of processing performance on AMD CPU and GPU processors to accelerate advanced research programs addressing the most complex compute problems. “The combination of a flexible compute infrastructure, scalable HPC and AI software, and the intelligent Slingshot system interconnect will enable Cray customers to undertake a new age of science, discovery and innovation at any scale.”

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.

Video: How to Scale from Workstation through Cloud to HPC in Cryo-EM Processing

Lance Wilson from Monash University gave this talk at the GPU Technology Conference. “We’ll review the last two years of development in single-particle cryo-electron microscopy processing, with a focus on accelerated software, and discuss benchmarks and best practices for common software packages in this domain. Our talk will include videos and images of atomic resolution molecules and viruses that demonstrate our success in high-resolution imaging.”