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ECP Launches “Let’s Talk Exascale” Podcast

The DOE’s Exascale Computing Project has launched a new podcast channel. In this episode, Danny Perez from Los Alamos National Laboratory discusses The Exascale Atomistic Capability for Accuracy, Length, and Time (EXAALT) project. EXAALT specializes in molecular dynamics simulations of materials. “We hope you enjoy the podcast, and we welcome your ideas for future episodes.”

Survey shows how AI Could Revolutionize Life Sciences

Some 44 per cent of life science professionals are using or experimenting with AI and deep learning, while 94 per cent expect an increase in use of machine learning within two years. These are findings from a survey carried out by the Pistoia Alliance, a global, not for profit alliance that works to lower barriers to innovation in life sciences R&D. “Our survey data shows that while life science professionals are already exploring how AI, ML and NLP can be used – there are clear gaps in the knowledge, data, and skills, which will enable more pharma and biotech companies to achieve tangible results from AI.”

Steve Oberlin from NVIDIA Presents: HPC Exascale & AI

Steve Oberlin from NVIDIA gave this talk at SC17 in Denver. “HPC is a fundamental pillar of modern science. From predicting weather to discovering drugs to finding new energy sources, researchers use large computing systems to simulate and predict our world. AI extends traditional HPC by letting researchers analyze massive amounts of data faster and more effectively. It’s a transformational new tool for gaining insights where simulation alone cannot fully predict the real world.”

New Whitepaper on Meltdown and Spectre fixes for HPC

Can you afford to lose a third of your compute real estate? If not, you need to pre-empt the impact of Meltdown and Spectre. “Meltdown and Spectre are quickly becoming household names and not just in the HPC space. The severe design flaws in Intel microprocessors that could allow sensitive data to be stolen and the fixes are likely to be bad news for any I/O intensive applications such as those often used in HPC. Ellexus Ltd, the I/O profiling company, has released a white paper: How the Meltdown and Spectre bugs work and what you can do to prevent a performance plummet.”

Adapting Deep Learning to New Data Using ORNL’s Titan Supercomputer

Travis Johnston from ORNL gave this talk at SC17. “Multi-node evolutionary neural networks for deep learning (MENNDL) is an evolutionary approach to performing this search. MENNDL is capable of evolving not only the numeric hyper-parameters, but is also capable of evolving the arrangement of layers within the network. The second approach is implemented using Apache Spark at scale on Titan. The technique we present is an improvement over hyper-parameter sweeps because we don’t require assumptions about independence of parameters and is more computationally feasible than grid-search.”

Visualization on GPU Accelerated Supercomputers

Peter Messmer from NVIDIA gave this talk at SC17. “This talk is a summary about the ongoing HPC visualization activities, as well as a description of the technologies behind the developer-zone shown in the booth.” Messmer is a principal software engineer in NVIDIA’s Developer Technology organization, working with clients to accelerate their scientific discovery process with GPUs.

Video: Deep Learning for Science

Prabhat from NERSC and Michael F. Wehner from LBNL gave this talk at the Intel HPC Developer Conference in Denver. “Deep Learning has revolutionized the fields of computer vision, speech recognition and control systems. Can Deep Learning (DL) work for scientific problems? This talk will explore a variety of Lawrence Berkeley National Laboratory’s applications that are currently benefiting from DL.”

Microsoft to acquire Avere Systems

Over at the Microsoft Blog, Jason Zander writes that the company is acquiring Avere Systems. “By bringing together Avere’s storage expertise with the power of Microsoft’s cloud, customers will benefit from industry-leading innovations that enable the largest, most complex high-performance workloads to run in Microsoft Azure. We are excited to welcome Avere to Microsoft, and look forward to the impact their technology and the team will have on Azure and the customer experience.”

Top 10 HPC White Papers for 2017: Machine Learning, AI, the Cloud & More

Many of the top 10 2017 HPC white papers deal with the next steps in the HPC journey, including moving to the cloud, and discovering the potential of machine learning and AI. The most downloaded reports of the year were written with industry partners such as Red Hat, Dell EMC, Intel, HPE and more.

Red Hat steps up with Multi-Architecture Solutions for HPC

In this video from SC17, Dan McGuan and Jon Masters from Red Hat describe the company’s Multi-Architecture HPC capabilities. “At SC17, you will have an opportunity to see the power and flexibility of Red Hat Enterprise Linux across multiple architectures, including Arm v8-A, x86_64 and IBM POWER Little Endian.”