...
Local research computing resources consist of <your number of compute servers> computational servers connected to a high-capacity shared storage server. The compute servers are <for example: a Dell PowerEdge R430 with dual 18-core/36-hyperthread CPUs and 384 GB RAM, and a Dell PowerEdge R410 with dual 4-core/8-hyperthread CPUs and 64 GB RAM; see this page for a list of servers on your POD and their configurations: POD Resources and Access#AvailablePODs>. The shared storage server is <for example, a 24-bay SuperMicro enclosure with 64GB RAM, or a 36-bay ThinkMate NearLine server with 128GB RAM> populated with <for example, 24 6-TB disks for 144 TB of raw storage and 80 TB usable.>. All <name of your group> data, including <for example, raw and processed data from NGS experiments>, user and administrative data, are stored on the shared storage server. The ZFS file system provides a large, contiguous address space, a high level of redundancy (2 of every 6 disks), automatic in-place data compression, and file system data integrity validation services. Compute servers communicate with the shared storage server over10-gigabit Ethernet, providing fast local storage for I/O intensive operations. Both compute and storage servers run Ubuntu Linux 18.04 server edition.
The compute and storage resources are housed at the University of Texas data center (UDC) and maintained and administered by our local Biomedical Research and Computing Facility (BRCF) group (see https://wikisutexas.utexasatlassian.edunet/wiki/display/RCTFusers/). The BRCF provisions all compute servers with a wide variety of bioinformatics tools and utilities, along with web-accessible versions of R Studio and Python JupyterHub. Other services the BRCF provides include automated weekly backups, periodic archiving of backup system data to the Ranch tape archive system at the Texas Advaced Computing Center (TACC), automated software deployment, operating system and hardware monitoring, and ongoing user support services.
...