1. UPPMAX and UPPNEX: Enabling high performance bioinformatics Ola Spjuth, UPPMAX ola.spjuth@farmbio.uu.se

2. High-performance bioinformatics Trivial/embarrassingly parallelizable – Mass of individual tasks (or divide up problems), run in parallel – E.g. analyze several sequences Non-trivial parallelism – Single task on many processors (data partitioning) – Example: Molecular dynamics

3. Resources for high-performance computing (HPC) Supercomputers – “a computer at the frontline of current processing capacity, particularly speed of calculation” Clusters – Processors in close proximity GRID computing – Distributed systems, (joined clusters)

9. UPPMAX Uppsala university’s resource for high performance computing (HPC) and related know-how – Computational clusters 6000 cores – Storage 1.4 PB parallel storage

10. A project at UPPMAX 13,152 MSEK from KAW/SNIC (2008-12-30) ~1 M cpuh/month on a shared cluster (kalkyl) ~1 PB cluster-attached parallel storage (bubo) Long term storage on SweStore (>1 PB) SMP machine, 64 core, 2TB RAM (halvan)

11. The cluster kalkyl 348 nodes with 8 cores each – 324 nodes with 24 GB – 16 nodes with 48 GB – 16 nodes with 72 GB – Total: 2784 cores SLURM queuing system

12. UPPNEX data flow

13. Knowledge Base / Community website www.uppnex.uu.se

14. UPPNEX Application Experts Assist with NGS Analysis Available via mailing-list or by direct contact

15. Project growth

16. UPPNEX storage usage

17. Used CPU core h / month 1 week maintenance stop for move to new computer hall

18. A typical day at UPPMAX

19. UPPNEX software used

20. Conclusions: Community needs (storage) Access to high-availability storage Access to long term storage Sustainable file infrastructure

21. Support new types of HPC users and usage Keep up with the bioinformatics software flood Managing data growth (previously only computations) Conclusions: UPPNEX main challenges