Huawei HPC Solution Selected by Ecological Modeling Lab for Cutting-edge Research
May 11, 2016
[Shenzhen, China, May 6, 2016] The Ecological Modeling Lab, led by Dr. George Arhonditsis in Toronto, has purchased a Huawei high-performance computing (HPC) solution for its cutting-edge research.
Researchers at the Ecological Modeling Lab at the University of Toronto Scarborough will use the Huawei high-performance computing (HPC) solution to perform four-dimensional (space and time) simulations associated with integrated watershed-receiving water body models.
The Department of Physical & Environmental Sciences has a great need for computational power and RAM memory that will be used to support the implementation of Bayesian inference techniques and other uncertainty analysis and parameter sampling (Markov Chain Monte Carlo, Latin Hypercube) methods. Therefore significant memory and storage capacity per HPC node are highly desirable.
Huawei provides HPC solution capabilities with optimized integrated software and hardware based on in-depth understanding about the HPC requirements of education and scientific research sectors. Huawei has built customized HPC platforms for universities and research institutes including the University of Warsaw (Poland), the Newcastle University (UK), and Uppsala University (Sweden). Huawei has also built joint innovation centers with strategic partners such as the Poznan Supercomputing and Networking Center (PSNC) of Poland, maintaining a long-term stable technical partnership.
Huawei’s HPC fat node solution is based on the Huawei FusionServer 8100 V3 8-socket mission critical server. With each node supporting up to 144 compute cores, the system supports a capacity of up to 12 TB memory. The system also supports 40G/100G high-speed Ethernet for computing-intensive applications. The solution not only meets the performance indicator requirements of complex computing models in various industries and applications, but also incorporates Huawei Reliability, Availability, and Serviceability (RAS) 2.0 technologies.
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