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Fujitsu & Linaro Collaborate to Accelerate HPC on ARM

“Developing a supercomputer that is many times faster than any of those currently available is clearly a challenging process and involves leveraging Fujitsu’s top hardware and software talent, as well as the help of partner companies such as ARM,” said Naoki Shinjo, SVP, Head of Next Generation Technical Computing Unit, Fujitsu.

Interview: Dr. Thomas Sterling on New Approaches to Efficient Supercomputing

In this video from KAUST, Professor Thomas Sterling, Professor of Intelligent Systems Engineering at Indiana University, shares his thoughts on new approaches to energy efficient supercomputing. “Our technical strategy focuses on the research and development of advanced technologies for extreme-scale computing and future exascale systems, including the following key elements: Execution Models; Runtime Systems; Graph Processing; Programming Interfaces; Compilers, Libraries, and Languages; Systems Architecture (Architecture, Power/Energy, Fault Tolerance, Networking), and Extreme Scale Applications and Visualization.”

Huawei: A Fresh Look at High Performance Computing

Francis Lam from Huawei presented this talk at the Stanford HPC Conference. “High performance computing is rapidly finding new uses in many applications and businesses, enabling the creation of disruptive products and services. Huawei, a global leader in information and communication technologies, brings a broad spectrum of innovative solutions to HPC. This talk examines Huawei’s world class HPC solutions and explores creative new ways to solve HPC problems.

Supermicro Deploys 30,000+ MicroBlade Servers for 1.06 PUE Datacenter

A technology-leading Fortune 100 company has deployed over 30,000 Supermicro MicroBlade servers, at its Silicon Valley data center facility with a Power Use Effectiveness (PUE) of 1.06, to support the company’s growing compute needs. Compared to a traditional data center running at 1.49 PUE, or more, the new datacenter achieves an 88percent improvement in overall energy efficiency. When the build out is complete at a 35 megawatt IT load power, the company is targeting $13.18M in savings per year in total energy costs across the entire datacenter.

Cray to Develop ARM-based Isambard Supercomputer for UK Met Office

“This is an exciting time in high performance computing,” said Prof Simon McIntosh-Smith, leader of the project and Professor of High Performance Computing at the University of Bristol. “Scientists have a growing choice of potential computer architectures to choose from, including new 64-bit ARM CPUs, graphics processors, and many-core CPUs from Intel. Choosing the best architecture for an application can be a difficult task, so the new Isambard GW4 Tier 2 HPC service aims to provide access to a wide range of the most promising emerging architectures, all using the same software stack.”

Bull Atos to Build for HPC Prototype for Mont-Blanc Project using Cavium ThunderX2 Processor

Today the Mont-Blanc European project announced it has selected Cavium’s ThunderX2 ARM server processor to power its new HPC prototype. The new Mont-Blanc prototype will be built by Atos, the coordinator of phase 3 of Mont-Blanc, using its Bull expertise and products. The platform will leverage the infrastructure of the Bull sequana pre-exascale supercomputer range for network, management, cooling, and power. Atos and Cavium signed an agreement to collaborate to develop this new platform, thus making Mont-Blanc an Alpha-site for ThunderX2.

Jülich Installs New QPACE3 Supercomputer for Quantum Chromodynamics

A new supercomputer has been deployed at the Jülich Supercomputing Center (JSC) in Germany. Called QPACE3, the new 447 Teraflop machine is named for “QCD Parallel Computing on the Cell. “QPACE3 is being used by the University of Regensburg for a joint research project with the University of Wuppertal and the Jülich Supercomputing Center for numerical simulations of quantum chromodynamics (QCD), which is one of the fundamental theories of elementary particle physics. Such simulations serve, among other things, to understand the state of the universe shortly after the Big Bang, for which a very high computing power is required.”

Fireside Chat: Dr. Eng Lim Goh on New Trends in HPC Energy Efficiency & Deep Learning

In this video from SC16, Dr. Eng Lim Goh from HPE/SGI discusses new trends in HPC Energy Efficiency and Deep Learning. “SGI’s leadership in data analytics derives from deep expertise in High Performance Computing and over two decades delivering many of the world’s fastest supercomputers. Leveraging this experience and SGI’s innovative shared and distributed memory computing solutions for data analytics enables organizations to achieve greater insight, accelerate innovation, and gain competitive advantage.”

SC16 to Showcase Latest Advances in HPC

SC16 returns to Salt Lake City on Nov. 13-18. The Six-day supercomputing event features internationally-known expert speakers, cutting-edge workshops and sessions, a non-stop student competition, the world’s largest supercomputing exhibition,panel discussions and much more. “No other annual event showcases the revolutionary advances and possibilities of high performance computing than the annual ACM/IEEE International Conference for High Performance Computing, Networking, Data Storage Analysis. From the impact of HPC on the future of medicine, to its transformative power in developing countries and “smart cities.” SC is the premiere venue for presenting leading-edge HPC research.”

Penguin Computing Adds Pascal GPUs to Open Compute Tundra Systems

“Pairing Tundra Relion X1904GT with our Tundra Relion 1930g, we now have a complete deep learning solution in Open Compute form factor that covers both training and inference requirements,” said William Wu, Director of Product Management at Penguin Computing. “With the ever evolving deep learning market, the X1904GT with its flexible PCI-E topologies eclipses the cookie cutter approach, providing a solution optimized for customers’ respective applications. Our collaboration with NVIDIA is combating the perennial need to overcome scaling challenges for deep learning and HPC.”