Implementation and experience with Big Red (a 30.7 TFLOPS IBM BladeCenter cluster), the Data Capacitor, and HPSS Craig A. Stewart 13 November 2007

License Terms Please cite this presentation as: Stewart, C.A. Implementation and experience with Big Red (a 30.7 TFLOPS IBM BladeCenter cluster), the Data Capacitor, and HPSS Presentation. Presented at: IU Display, SC2007 Exhibit Hall (Reno, NV, 13 Nov 2007). Available from: Portions of this document that originated from sources outside IU are shown here and used by permission or under licenses indicated within this document. Items indicated with a © are under copyright and used here with permission. Such items may not be reused without permission from the holder of copyright except where license terms noted on a slide permit reuse. Except where otherwise noted, the contents of this presentation are copyright 2007 by the Trustees of Indiana University. This content is released under the Creative Commons Attribution 3.0 Unported license ( This license includes the following terms: You are free to share – to copy, distribute and transmit the work and to remix – to adapt the work under the following conditions: attribution – you must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work). For any reuse or distribution, you must make clear to others the license terms of this work.

Outline Brief history of implementation in TeraGrid and at IU System architecture Performance analysis User experience and science results Lessons learned to date

Image from IU & TeraGrid IU: 2 core campuses, 6 regional campuses President: Michael A. McRobbie Advanced computing: University Information Technology Services, Pervasive Technology Labs, School of Informatics Motivation for being part of TeraGrid: Support national research agendas Improve ability of IU researchers to use national cyberinfrastructure Testbed for IU computer science research

Big Red - Basics and history IBM e1350 BladeCenter Cluster, SLES 9, MPICH, Loadleveler, MOAB Spring 2006: 17 days assembly at IBM facility, disassembled, reassembled in 10 days at IU TFLOPS peak theoretical, achieved on Linpack; 23rd on June 2006 Top500 List (IU’s highest listing to date). In production for local users on 22 August 2006, for TeraGrid users 1 October 2006 Upgraded to TFLOPS Spring 2008; now 42nd on Top500 List Named after nickname for IU sports teams

Data Capacitor - Basics and History Initially funded by $1.7M NSF grant to IU Initially 535 TB of spinning disk - soon to be expanded to more than 1 PB Designed as a temporary holding place for large data sets - a novel type of storage system Uses Lustre file system

HPSS - Basics and History High Performance Storage System Designed initially by IBM and 5 DOE labs IU has contributed code, remains the only unclassified HPSS implementation with distributed storage Data written to HPSS is by default copied to IUB and IUPUI

Feature20.4 TFLOPS30.7 TFLOPS Computational hardware, RAM JS21 componentsTwo 2.5 GHz PowerPC 970MP processors, 8 GB RAM, 73 GB SAS Drive, 40 GFLOPS Same No. of JS21 blades No. of processors; cores1,024 processors; 2,048 processor cores 1,536 processors; 3,072 processor cores Total system memory4 TB6 TB Disk storage GPFS scratch space266 TBSame Lustre535 TBSame Home directory space25 TBSame Networks Total outbound network bandwidth40 Gbit/secSame Bisection bandwidth64 GB/sec - Myrinet GB/sec - Myrinet 2000

Motivations and goals Initial goals for TFLOPS system: Local demand for cycles exceeded supply TeraGrid Resource Partner commitments to meet Support life science research Support applications at 100s to 1000s of processors 2nd phase upgrade to TFLOPS Support economic development in State of Indiana

Why a PowerPC-based blade cluster? Processing power per node Density, good power efficiency relative to available processors Possibility of performance gains through use of Altivec unit & VMX instructions Blade architecture provides flexibility for future Results of Request for Proposals process ProcessorTFLOPS/ MWatt MWatts/ PetaFLOPS Intel Xeon AMD PowerPC 970 MP (dual core)

Difference: 4 KB vs 16 MB page size Linpack performance Benchmark set NodesPeak Theoretical TFLOPS Achieved TFLOPS % HPCC Top Top

HPCC and Linpack Results (510 nodes) G-HPLG- PTRANS G- Random Access G-FFTEEP- STREAM Sys EP- STREAM Triad EP- DGEMM Random Ring Bandwidth Random Ring Latency GB/susec TFlop/sGB/sGup/sGFlop/sGB/s GFlop/s Total Per processor Data posted to

September 23, TFLOPS e1350 (Big Red) vs. a Cray XT3 at Oak Ridge National Labs, including 5200 single core 2.4 GHz AMD Opteron processors (left), and a 2.09 TFLOPS HP XC4000 owned by HP, Inc., including 256 dual-core ADM Opteron processors (right).

Elapsed time per simulation timestep among best in TeraGrid

Bandwidth Challenge SC|2006

Competition Performance During testing 4 x 2 trunked 1 Gb lines 32 GB in 34 seconds - 941MB/s Competition All four experiments Sustained Gb

HPSS I/O Speed Growth

Simulation of TonB-dependent transporter (TBDT) Used systems at NCSA, IU, PSC Modeled mechanisms for allowing transport of molecules through cell membrane Work by Emad Tajkhorshid and James Gumbart, of University of Illinois Urbana-Champaign. Mechanics of Force Propagation in TonB- Dependent Outer Membrane Transport. Biophysical Journal 93: (2007) To view the results of the simulation, please go to: TonB-BtuB/btub-2.5Ans.mpg Image courtesy of Emad Tajkhorshid

ChemBioGrid Analyzed 555,007 abstracts in PubMed in ~ 8,000 CPU hours Used OSCAR3 to find SMILES strings -> SDF format -> 3D structure (GAMESS) - > into Varuna database and then other applications “Calculate and look up” model for ChemBioGrid

WxChallenge ( Over 1,000 undergraduate students, 64 teams, 56 institutions Usage on Big Red: ~16,000 CPU hours on Big Red 63% of processing done on Big Red Most of the students who used Big Red couldn’t tell you what it is Integration of computation and data flows via Lustre (Data Capacitor)

Overall user reactions NAMD, WRF users very pleased Porting from Intel instruction set a perceived and sometimes real challenge in a cycle-rich environment MILC optimization with VMX not successful so far in eyes of user community Keys to biggest successes: Performance characteristics of JS21 nodes Linkage of computation and storage (Lustre - Data Capacitor) Support for grid computing via TeraGrid

Evaluation of implementation The manageability of the system is excellent For a select group of applications, Big Red provides excellent performance and reasonable scalability We are likely to expand bandwidth from Big Red to the rest of the IU cyberinfrastructure Quarry is a critical companion to Big Red; without Quarry Big Red would not be bnearly so successful Focus on data management and scalable computation critical to success Next steps: industrial partnerships and economic development in Indiana

Conclusions A 30.7& TFLOPS system with “not the usual” processors was successfully implemented serving local Indiana University researchers, and the national research audience via the TeraGrid Integration of computation and data management systems was critical to success In the future Science Gateways will be increasingly important: Most scientists can’t constantly chase after the fastest available system; gateway developers might be able to Programmability of increasingly unusual architectures not likely to become easier For applications with broad potential user bases, or extreme scalability on specialized systems, Science Gateways will be critical in enabling transformational capabilities and supporting scientific workflows. Achieving broad use can only be achieved by relieving scientists of need to understand details of systems

Acknowledgements - Funding Sources IU’s involvement as a TeraGrid Resource Partner is supported in part by the National Science Foundation under Grants No. ACI l, OCI , OCI , and OCI The IU Data Capacitor is supported in part by the National Science Foundation under Grant No. CNS This research was supported in part by the Indiana METACyt Initiative. The Indiana METACyt Initiative of Indiana University is supported in part by Lilly Endowment, Inc. This work was supported in part by Shared University Research grants from IBM, Inc. to Indiana University. The LEAD portal is developed under the leadership of IU Professors Dr. Dennis Gannon and Dr. Beth Plale, and supported by NSF grant The ChemBioGrid Portal is developed under the leadership of IU Professor Dr. Geoffrey C. Fox and Dr. Marlon Pierce and funded via the Pervasive Technology Labs (supported by the Lilly Endowment, Inc.) and the National Institutes of Health grant P20 HG Many of the ideas presented in this talk were developed under a Fulbright Senior Scholar’s award to Stewart, funded by the US Department of State and the Technische Universitaet Dresden. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF), National Institutes of Health (NIH), Lilly Endowment, Inc., or any other funding agency

Acknowledgements - People Research and Technical Services Division Staff generally, High Performance Systems, High Performance Applications, Research Storage, and Team Data Capacitor particularly Malinda Lingwall for editing, graphic layout, and managing process Maria Morris contributed to the graphics used in this talk Marcus Christie and Surresh Marru of the Extreme! Computing Lab contributed the LEAD graphics John Morris ( and Cairril Mills (Cairril.com Design & Marketing) contributed graphics Rick McMullen and all the Huffmans (CIMA) Randy Bramley and Marie Ma (Obsidian) Mookie Baik and Yogita Mantri (Chemistry) Beth Plale, Dennis Gannon, AJ Ragusa, Suresh Marru, Chathura Herath (LEAD) Doug Balog, Derek Simmel (PSC) Guido Juckeland, Robert Henschel, Matthias Mueller (ZIH) This work would not have been possible without the dedicated and expert efforts of the staff of the Research Technologies Division of University Information Technology Services, the faculty and staff of the Pervasive Technology Labs, and the staff of UITS generally. Thanks to the faculty and staff with whom we collaborate locally at IU and globally (via the TeraGrid, and especially at Technische Universitaet Dresden)

Thank you Any questions?