Cancer Research UK is using Platform LSF to help drive forward its human genome research project at the Cambridge Research Institute (CRI).
Platform LSF is the most powerful workload manager available for high performance computing (HPC) environments and scientific computing. By integrating Platform LSF, a workload manager for HPC environments and scientific computing, with a new advanced genetic sequencing platform, the institute has gained greater insight into genetic cancer mutations that will lead to scientific breakthroughs in the areas of cancer diagnosis, treatment and prevention.
'Platform LSF gives us the means to produce and manage a wealth of gene sequencing data that we could only have dreamed about previously,' said Peter Maccallum, head of IT and scientific computing at Cancer Research UK in Cambridge. 'This has already lead to tangible published work looking into breast cancer, and is proving its worth in helping our researchers further the understanding of how cancers progress.'
Prior to implementing Platform LSF, CRI’s 21 research groups employed separate computing resources in separate locations, which drove up server costs, reduced utilisation rates and increased server maintenance. By orchestrating workloads and managing CRI’s research applications in a single data centre, Platform LSF has enabled CRI to save approximately £50,000 by removing hardware and maintenance duplication across each location, while increasing the amount of data processed. The institute can now direct more computing resources directly to its research teams to use in a more timely and cost efficient manner.
CRI has already saved the equivalent in man hours of one full-time employee by integrating Platform LSF. As a result, the institute plans to scale Platform LSF internally by adding more servers as compute requirements increase. CRI is also collaborating with Platform Computing to architecturally support cross-organisation systems for HPC clusters that will enable CRI to collaborate with other research organisations in order to meet the growing demand for genomics research.
