“Computational science has come a long way with machine learning (ML) and deep learning (DL) in just the last year. Leading centers of high-performance computing are making great strides in developing and running ML/DL workloads on their systems. Users and algorithm scientists are continuing to optimize their codes and techniques that run their algorithms, while system architects work out the challenges they still face on various system architectures. At SC16, I had the honor of hosting three of HPC’s thought leaders in a panel to get their ideas about the state of Artificial Intelligence (AI), today’s challenges with the technology, and where it’s going.”
“Through multiscale simulation of the circulatory system, it is now possible to model this surgery and optimize it using the state of the art optimization techniques. In-silico analysis has allowed us to test new surgical design without posing any risk to patient’s life. I will show the outcome of this study, which is a novel surgical option that may revolutionize current clinical practice.”
Today ISC 2017 announced that data scientist, Prof. Dr. Jennifer Tour Chayes from Microsoft Research will give the opening keynote at the conference. “I’ll discuss in some detail two particular applications: the very efficient machine learning algorithms for doing collaborative filtering on massive sparse networks of users and products, like the Netflix network; and the inference algorithms on cancer genomic data to suggest possible drug targets for certain kinds of cancer,” explains Chayes.
Intel DAAL is a high-performance library specifically optimized for big data analysis on the latest Intel platforms, including Intel Xeon®, and Intel Xeon Phi™. It provides the algorithmic building blocks for all stages in data analysis in offline, batch, streaming, and distributed processing environments. It was designed for efficient use over all the popular data platforms and APIs in use today, including MPI, Hadoop, Spark, R, MATLAB, Python, C++, and Java.
“It is extremely important that customers using the Veloce emulation platform maximize the usability of their datacenter-based emulation resources,” said Eric Selosse, vice president and general manager of the Mentor Emulation Division. “We’ve worked with Univa on a tight integration between Univa Grid Engine and the Veloce Enterprise Server App to streamline the workload management task.”
Today UK-based ebb3 announced that Emerson Automation Solutions is deploying high-performance software for the oil and gas industry virtually using ebb3’s remote visualization technology. “The Roxar reservoir management software has to handle very large models, and many models simultaneously for uncertainty analysis,” Robert Frost, Product Development Manager at Emerson. “The more refined these are, the more graphical processing is required. This is one of the most challenging areas of virtualization, and virtual desktops with the power to support such high-powered graphics are almost unheard of. Along with the platform and partnership services that ebb3 provides, the power they’ve harnessed for virtual access to 3D visualization software is impressive. Being able to keep data in the data centre for fast access without compromising visualization and usability is a huge step forward.”
Hagen Toennies from Gaikai Inc. presented these Best Practices at the 2017 HPC Advisory Council Stanford Conference. “In this talk we will present how we enable distributed, Unix style programming using Docker and Apache Kafka. We will show how we can take the famous Unix Pipe Pattern and apply it to a Distributed Computing System.”
The Penn State Cyber-Laboratory for Astronomy, Materials, and Physics (CyberLAMP) is acquiring a high-performance computer cluster that will facilitate interdisciplinary research and training in cyberscience and is funded by a grant from the National Science Foundation. The hybrid computer cluster will combine general purpose central processing unit (CPU) cores with specialized hardware accelerators, including the latest generation of NVIDIA graphics processing units (GPUs) and Intel Xeon Phi processors.
In this RCE Podcast, Brock Palen and Jeff Squyres speak with the creators of SAGE2 Scalable Amplified Group Environment. SAGE2 is a browser tool to enhance data-intensive, co-located, and remote collaboration. “The original SAGE software, developed in 2004 and adopted at over one hundred international sites, was designed to enable groups to work in front of large shared displays in order to solve problems that required juxtaposing large volumes of information in ultra high-resolution. We have developed SAGE2, as a complete redesign and implementation of SAGE, using cloud-based and web-browser technologies in order to enhance data intensive co-located and remote collaboration.”
“Increased system size and a greater reliance on utilizing system parallelism to achieve computational needs, requires innovative system architectures to meet the simulation challenges. As a step towards a new network class of co-processors intelligent network devices, which manipulate data traversing the data-center network, SHARP technology designed to offload collective operation processing to the network. This tutorial will provide an overview of SHARP technology, integration with MPI, SHARP software components and live example of running MPI collectives.”