In a blog on the Lenovo site, Andrew Richards, Head of Advanced Research Computing, University of Oxford, explains why the university chose for Lenovo as an HPC system: "After shortlisting three potential vendors, we chose to deploy Lenovo NeXtScale System M5 with 5,440 Intel processor cores. Not only did this offer far greater processing power than the other offerings, it was also much cheaper in terms of the total cost of ownership over three years." The system takes less than 11 kW per rack. Read further...

At the SC15 site , David Wheeler explains what it takes to build SCINET at the SC supercomputing conference. "SCinet is always pushing the limits of network innovation and operations. This year SCinet is provisioning production Software-Defined Networking (SDN) circuits to the exhibit floor booths, providing smarter, dynamically manageable connections. We are very excited to see the turn out for this project." This year, SCinet will install 80-90 miles (about 140 Kiliometres) of fiber within the Austin Convention Center. With SCinet supporting more than 10,000 attendees and 330 booths, Wheeler expects to need 15 tons of cooling and around 30KW of power at 480V. SCInet will again supply more than 1 Terabit of bandwidth, donated from vendors and neighboring research and education networks. Read further...

At the beginning of 2016 the Journal of Computer Physics Communications (Elsevier, JCR:3.122, Q1) will close a Special Issue on HPC for Advanced Modeling and Simulation of Materials. Topics include: Numerical methods and parallel algorithms for the advanced modeling and simulation of materials; Use of hardware accelerators (MIC, GPUs, FPGA) and heterogeneous hardware in computational material science'Mathematical modeling and high performance computing tools in large-scale material simulation. Read further...

Bright Computing has published a case study about their University of Colorado use case. The Department of Mechanical Engineering, University of Colorado at Boulder, uses "Prospero", its HPC cluster for research projects, like improving decision support tools through inverse modeling and sensitivity analysis; constraining ammonia distributions through remote sensing, modeling and surface observations; accounting for costs of air quality and climate impacts on the future US electricity mix; and looking at sources of nitrate in Antarctica. Bright Cluster Manager helped the University eliminate issues with their management platform, like losing IPMI access, skipped nodes, trouble creating and moderating user accounts, and queue manager problems. Read further...