Research highlights: Running climate models in the cloud

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Xianglei Huang

Can cloud computing systems help make climate models easier to run? Assistant research scientist Xiuhong Chen and MICDE affiliated faculty Xianglei Huang, from Climate and Space Sciences and Engineering (CLASP), provide some answers to this question in an upcoming issue of Computers & Geoscience (Vol. 98, Jan. 2017, online publication link: http://dx.doi.org/10.1016/j.cageo.2016.09.014).

Teaming up with co-authors Dr. Chaoyi Jiao and Prof. Mark Flanner, also in CLASP, as well as Brock Palen and Todd Raeker from U-M’s Advanced Research Computing – Technology Services (ARC-TS), they compared the reliability and efficiency of Amazon’s Web Service – Elastic Compute 2 (AWS EC2) with U-M’s Flux high performance computing (HPC) cluster in running the Community Earth System Model (CESM), a flagship climate model in the U.S. developed by the National Center for Atmospheric Research.

The team was able to run the CESM in parallel on an AWS EC2 virtual cluster with minimal packaging and code compiling effort, finding that the AWS EC2 can render a parallelization efficiency comparable to Flux, the U-M HPC cluster, when using up to 64 cores. When using more than 64 cores, the communication time between virtual EC2 exceeded the distributed computing time.

Until now, climate and earth systems simulations had relied on numerical model suites that run on thousands of dedicated HPC cores for hours, days or weeks, depending on the size and scale of each model. Although these HPC resources have the advantage of being supported and maintained by trained IT support staff, making them easier to use them, they are expensive and not readily available to every investigator that needs them.

Furthermore, the systems within reach are sometimes not large enough to run simulations at the desired scales. Commercial cloud systems, on the other hand, are cheaper and accessible to everyone, and have grown significantly in the last few years. One potential drawback of cloud systems is that the user needs to provide and install all the software and the IT expertise needed to run the simulations’ packages.

Chen and Huang’s work represents an important firstxiangleihuangpost2016 step in the use of cloud computing in large-scale climate simulations. Now, cloud computing systems can be considered a viable alternate option to traditional HPC clusters for computational research, potentially allowing researchers to leverage the computational power offered by a cloud environment.

This study was sponsored by the Amazon Climate Initiative through a grant awarded to Prof. Huang. The local simulation in U-M was made possible by a DoE grant awarded to Prof. Huang.

Top image: http://www.cesm.ucar.edu/

Scientific Computing Student Club (SC2) working on XSEDE Hybrid Computing challenge

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XSEDEHybridBootcamp2016

After learning about hybrid computing at XSEDE’s summer bootcamp, the Scientific Computing Student Club (SC2) is working as a team on the XSEDE hybrid computing challenge: How fast can you run a 10K x 10K Laplace code to convergence using openMP, openACC and MPI?

This year’s challenge winner will get an NVIDIA K40 GPU. If the SC2 wins the challenge, the K40 will be used to start the clubs own allocation for club-based programming challenges and other test code, benchmarking, etc.

The challenge runs through July 8, 2016. If you are interested in participating, send an email to sc2members@umich.edu.

New MICDE associate directors named

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MICDE is pleased to announce the appointment of three new associate directors starting July 1, 2016: Karthik Duraisamy (Aerospace Engineering),  Annette Ostling (Ecology and Environmental Biology) and Siqian Shen (Industrial and Operations Engineering). The associate directors, together with MICDE Director Krishna Garikipati and Assistant Director Mariana Carrasco-Teja, will work on initiatives to help MICDE achieve its goals. These include growing MICDE’s educational programs, the Ph.D in Scientific Computing and the Graduate Certificate in Computational Discovery & Engineering; assembling interdisciplinary research teams and helping them secure funding for their projects; engaging with industrial partners; and coordinating outreach activities.