14 Nov 2017 Chicago - Univa's Univa Grid Engine distributed resource management system is powering the Wellcome Centre for Human Genetics' (WHG) high performance computing (HPC) environment.
WHG is a research institute within the Nuffield Department of Medicine at the University of Oxford. The Centre is an international leader in genetics, genomics, statistics and structural biology with more than 400 researchers and 70 administrative and support personnel. WHG's mission is to advance the understanding of genetically-related conditions through a broad range of multi-disciplinary research.
To support its research community, the Centre operates a shared HPC cluster comprising over 4,000 InfiniBand-connected, high-memory compute cores and 4PB of high performance, parallel storage running 250 applications. WHG's previous open source scheduler lacked practical software support and did not address the increasing use of containerized machine learning applications. To plan for growth and accommodate mixed workload types - serial-batch, array, MPI, container, Spark - on the same shared cluster, the Centre evaluated a variety of open source and commercial options. The review committee awarded Univa Grid Engine as the replacement, citing its modern scheduler, expert technical support and minimal user re-training for its selection.
"The conversion from the previous scheduler to Univa Grid Engine was virtually painless. Our users are happy that their hard-won knowledge continues to be relevant, significant scheduler bugs and vulnerabilities were fixed, and we also save on our own precious system administration time", stated Dr. Robert Esnouf, Head of Research Computing Core, Wellcome Centre for Human Genetics. "We can now plan for significant future growth with Univa as a key component of our infrastructure offering."
The transition to Univa Grid Engine also provided WHG with new capabilities like GPU-aware scheduling, DRMAA2, and container support, placing WHG in a position to embrace emerging research techniques and support a wider range of research. To learn more how WHG expanded workloads for their life-science research, you can download a detailed case study .