UPPMAX and UPPNEX:Enabling high performance bioinformatics

Ola Spjuth, UPPMAX

ola.spjuth@farmbio.uu.se

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

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)

UPPMAX

• Uppsala university’s resource for high performance computing (HPC) and related know-how– Computational clusters

• 6000 cores– Storage

• 1.4 PB parallel storage

• 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)

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

UPPNEX data flow

Knowledge Base / Community website

www.uppnex.uu.se

UPPNEX Application Experts

• Assist with NGS Analysis

• Available viamailing-list or by direct contact

Project growth

UPPNEX storage usage

Used CPU core h / month

1 week maintenance stop for move to new computer hall

A typical day at UPPMAX

UPPNEX software used

Conclusions:Community needs (storage)

• Access to high-availability storage

• Access to long term storage

• Sustainable file infrastructure

• 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