The Center for Quantitative Life Sciences (CQLS) maintains an extensive and well-managed computational research infrastructure consisting of a distributed service architecture, a greater than 6000-processor computer cluster and a secure private 1G/10G/40G/100G network (see figure 1). Each machine has internal hard drive disk space for operating system and scratch, but is also connected to 8.5PB of NFS shared disk space. The CQLS encourages high-volume users to contribute to the computational infrastructure. Users are charged $75, $138, and $201 per/month for maintaining each processing machine, web/database server, and file server, respectively. The nodes are provided at the highest priority to the specific project and provided upon request at a lower priority to other CQLS researchers. Thus, subsets of cluster nodes are dedicated to specific research projects, but they function as part of a unified cluster when needed for intensive jobs for research projects that could not otherwise be done. This priority-based scheduling has proven quite successful, both in terms of end-user satisfaction and in the execution of systems administration activities. Computational requirements are constantly re-evaluated and new hardware is integrated as needed.
The CQLS maintains an active biocomputing group consisting of full-time staff. Kenneth Lett serves as the CQLS systems administrator and infrastructure manager. Kenneth has extensive expertise in all aspects of hardware and infrastructure design and maintenance. Kenneth also has experience in software development and bioinformatics applications. Matthew Peterson maintains CQLS data flow from the Core Lab and teaches in the ACTF. Dr. Andrew Black, in addition to participating in research projects, also serves as a bioinformatics trainer. Dr. Andrew Black offers training courses in computer programming, runs topical workshops, facilitates peer-to-peer training, and runs the OSU bioinformatics users group. Dr. Kronmiller serves as a bioinformatics consultant. The efforts of the CQLS biocomputing group are directed towards facilitating biological research through the use of computational tools. Projects span from CQLS Core Labs ordering and data management software to developing tools and procedures for analysis and distribution of high-throughput DNA sequencer data. The CQLS computational groups continually works to lower the activation energy needed by researchers to take advantage of the computing resources and creates new tools to help this process. Finally, the CQLS bioinformatics group actively foster collaborative projects with University faculty associated with the Center.
CQLS HPC and Biocomputing Resources
Number of Processors
Shared Disk Space
Uninterruptable Power Supply
Average Number of Processing Jobs per Day
Total Memory Across HPC Cluster
Public and Private Network (WAN and LAN)