A Scalable Distributed Datastore for BioImaging R. Cai, J. Curnutt, E. Gomez, G. Kaymaz, T. Kleffel, K. Schubert, J. Tafas {jcurnutt, egomez, keith,

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Presentation transcript:

A Scalable Distributed Datastore for BioImaging R. Cai, J. Curnutt, E. Gomez, G. Kaymaz, T. Kleffel, K. Schubert, J. Tafas {jcurnutt, egomez, keith, Renaissance Research Labs Department of Computer Science California State University San Bernardino, CA Supported by NSF ITR #

Background CSUSB Institute for Applied Supercomputing Low Latency Communications UCSB Center for BioImage Informatics Retinal images Texture map searches Distributed consortium (UCB, CMU)

Retina Images Normal (n) 3 month detachment (3m) 1 day detachment followed by 6 day reattached with increased oxygen (1d+6dO2) 3 day detachment (3d) Laser scanning confocal microscope images of the retina

Environment UCSB Raven Cluster Image and metadata server search external internal BISQUE features analysis Hammer/Nail Cluster Local LAN CSUSB Image and metadata server Image and metadata server WAN Local Lustre

Software Open source OME Postgresql 7 Bisque Distributed datastore Clustering NFS Lustre Benchmark: OSDB

Hardware - Raven 5 year old dual processor 1.4 GHz Pentium 3 256MB RAM 60GB SCSI Compaq Proliant DL-360 servers. Raven has been latency tuned.

Hardware – Hammer/Nail UCSB CSUSB Hammer headnode 5 Nail nodes quad CPUs 3.2 Ghz Xeon 4GB RAM 140GB SCSI Dell servers Bandwidth tuned (default)

Outline Effect of node configuration Comparison of network file systems Effects of a wide area network (WAN)

Relative LAN Performance

NFS LAN/WAN Performance

Design Effects? A few expert users Metadata searches Small results to user Texture searches Heavy calculation on cluster Small results to user Latency tuning

Outline Effect of node configuration Comparison of network file systems Effects of a wide area network (WAN)

NFS / Luster Performance. NFS well known standard Configuration problems with OME performance comparison of the Lustre file system Lustre Journaling Stripe across multiple computers Data redundancy and failover

Relative Performance on LAN NSF/Lustre Compared to local DB 1GB LAN two significant differences

Significant Differences NSF caching bulk deletes and bulk modifies Lustre stripes across computers increase the bandwidth

Outline Effect of node configuration Comparison of network file systems Effects of a wide area network (WAN)

Effect on Wide Area Network WAN Compared three connections Local Switched, high speed LAN (1 Gb/s) WAN between UCSB and CSUSB (~50 Mb/s) NFS only UCSB didn’t have Lustre installed Active research prevented reinstalling OS

Local/LAN/WAN Performance

Effect on Wide Area Network WAN Most significant effect Not bandwidth intensive operations Latency intensive operation Next generation WAN will not solve the problem. Frequently used data must be kept locally Database cluster Daily sync of remote databases

Conclusions Scientific researchers Latency tune network Don’t bandwidth tune Latency of WAN is too large replicate data and update. Bisque/OME NFS issues Lustre High bandwidth operations Stripe Lustre across systems

Future directions: Agent based texture search engine Loosely coupled cluster WAN connection Unreliable connection Fault tollerant Parallelize Jobs Open source components Scilab Convert NSF funded algorithms in Matlab Simple interface Superior caching scheme for Lustre

Questions…