2019-04-10 Projects filesystem expansion complete

The expansion and maintenance of the /projects2 filesystem has been completed, and all access has been restored.

CCS AC
hpc@ccs.miami.edu

2019-02-05 CG Campus network upgrades complete

CCS network upgrades have completed and access has been restored.

CCS AC
hpc@ccs.miami.edu

2018-10-13 Network maintenance complete

CCS network maintenance has completed and access has been restored.

CCS AC
hpc@ccs.miami.edu

2018-09-21 File system access restored

/scratch and /projects file system access has been restored.

CCS AC
hpc@ccs.miami.edu

2018-06-26 CCS Storage system maintenance, July 3rd – complete

Storage maintenance complete and all access has been restored.

CCS AC
hpc@ccs.miami.edu

HPC

The High-Performance Computing (HPC) core is focused on providing the latest in Supercomputing technology and tools to the University of Miami (UM) research community. While this core consists of traditional operations staff such as systems and network administrators, it also encompasses other areas of expertise including scientific programmers, parallel code profiling, and optimization. The HPC core is responsible for the operations of all infrastructure maintained at CCS.

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The HPC core’s services include batch and interactive Compute, Visualization and Secure Data Processing clusters, Systems Administration and Consulting, Storage Implementation, Archive Storage, Systems Hosting and Maintenance. The HPC core has in-depth experience in parallelizing codes written in Fortran, C, Java, Perl, Python, and R. The core also has expertise in parallelizing code using both MPI and OpenMP.

Central to HPC is the Pegasus Supercomputer, a 350-node Lenovo cluster with over 300 applications and optimized libraries, including standard scientific libraries and numerous optimized libraries and algorithms tuned for the computing environment. The LSF (load sharing facility) resource manager, which supports over 1500 users and over 200,000 simultaneous job submissions, maximizes the efficiency of computational resources. By utilizing the full suite of LSF tools, we are able to provide for both batch and interactive jobs while retaining workload management features.

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