Abstract
IBM’s Blue Gene supercomputer has evolved through three generations from the original Blue Gene/L to P to Q. A higher level of integration has enabled greater single-core performance, and a larger concurrency per compute node. Although these changes have brought with them a higher overall system peak-performance, no study has examined in detail the evolution of performance across system generations. In this work we make two significant contributions – that of providing a comparative performance analysis across Blue Gene generations using a consistent set of tests, and also in providing a validated performance model of the NEK-Bone proxy application. The combination of empirical analysis and the predictive performance model enable us to not only directly compare measured performance but also allow for a comparison of system configurations that cannot currently be measured. We provide insights into how the changing characteristics of Blue Gene have impacted on the application performance, as well as what future systems may be able to achieve.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Green500, http://www.green500.org/
Allen, F., et al.: Blue Gene: A Vision for Protein Science using a Petaflop Supercomputer. IBM Sys. J. 40(2), 310–327 (2001)
Almasi, G., et al.: Demonstrating the Scalability of a Molecular Dynamics Application on a Petaflops Computer. Int. J. of Parallel Programming 30(4), 317–351 (2002)
Almasi, G., et al.: Dissecting Cyclops: A Detailed Analysis of a Multithreaded Architecture. ACM SIGARCH Computer Architecture News 31(1), 26–38 (2003)
Adiga, N.R., et al.: An Overview of the Blue Gene/L Supercomputer. In: Proc. IEEE/ACM Supercomputing, SC 2002, Baltimore (2002)
Chen, D., et al.: QCDOC: A 10-Teraflops Scale Computer for Lattice QCD. Nucl. Phys. B 94(1-3), 825–832 (2001)
Boyle, P.A., Chen, D., et al.: QCDOC: A 10 Teraflops Computer for Tightly-Coupled Calculations. In: Proc. IEEE/ACM Supercomputing (SC 2004), Pittsbugh (2004)
Davis, K., Hoisie, A., Johnson, G., Kerbyson, D.J., Lang, M., Pakin, S., Petrini, F.: A Performance and Scalability Analysis of the BlueGene/L Architecture. In: SC 2004, Pittsburgh (2004)
Almasi, G., et al.: Unlocking the Performance of the BlueGene/L Supercomputer. In: Proc. IEEE/ACM Supercomputing (SC 2004), Pittsburgh (2004)
IBM Blue Gene Staff: Overview of the IBM Blue Gene/P Project. IBM J. Res. & Dev. (1/2), 199–220 (2008)
Haring, R.A., Ohmacht, M., Fox, T.W., et al.: The IBM Blue Gene/Q Compute Chip. IEEE Micro, 48–60 (2012)
Chen, D., Choudhury, A., Eisley, N., et al.: Looking Under the hood of the Blue Gene/Q Network. In: Proc. IEEE/ACM Supercomputing (SC 2012), Salt Lake City (2012)
H.: Terascale Spectral Element Algorithms and Implementations. In: Proc. IEEE/ACM Supercomputing (SC 1999), Portland (1999)
P-SNAP v1.2, http://www.c3.lanl.gov/pal/software
McCalpin, J.: Memory bandwidth and machine balance in current high performance computers. In: IEEE Tech. Committee on Computer Architecture (TCCA), pp. 19–25 (1995)
Barker, K.J., Davis, K., Hoisie, A., Kerbyson, D.J., Lang, M., Pakin, S., Sancho, J.C.: Using performance modeling to design large-scale systems. IEEE Computer 42(11), 42–49 (2009)
Chen, D., Eisley, N.A., Heidelberger, P., et al.: The IBM Blue Gene/Q Interconnection Fabric. IEEE Micro 32(1), 32–43 (2012)
Chen, D., Eisley, N.A., Heidelberger, P., et al.: The IBM Blue Gene/Q Interconnection Network and Message Unit. In: Proc. IEEE/ACM Supercomputing, SC 2011, Seattle (2011)
Saini, S., Naraikin, A., Biswas, R., Barkai, D., Sandstrom, T.: Early Performance Evaluation of Nehalem Cluster Using Scientific and Engineering Applications. In: SC 2009, Portland (2009)
Hoisie, A., Johnson, G., Kerbyson, D.J., Lang, M., Pakin, S.: A Performance Comparison through Benchmarking and Modeling of Three Leading Supercomputers: Blue Gene/L, Red Storm, and Purple. In: Proc. IEEE/ACM Supercomputing (SC 2006), Tampa (2006)
Kerbyson, D.J., Hoisie, A.: Performance Modeling of the Blue Gene Architecture. In: IEEE John Vincent Atanasoff Int. Symp. on Modern Computing, Sofia, Bulgaria (2006)
Bhatele, A., Wesolowski, L., Bohm, E., Solomonik, E., Kale, L.V.: Understanding application performance via micro-benchmarks on three large supercomputers: Intrepid, Ranger and Jaguar. In: Int. J. of High Performance Computing Applications, IJHPCA (2010)
Rodrigues, R.F., et al.: The Structural Simulation Toolkit. ACM Sigmetrics Performance Evaluation Review 38(4), 37–42 (2011)
Zheng, G., Kakulapati, G., Kale, L.V.: BigSim: A Parallel Simulator for Performance Prediction of Extremely Large Machines. In: Proc. IPDPS, Santa Fe (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kerbyson, D.J. et al. (2013). Tracking the Performance Evolution of Blue Gene Systems. In: Kunkel, J.M., Ludwig, T., Meuer, H.W. (eds) Supercomputing. ISC 2013. Lecture Notes in Computer Science, vol 7905. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38750-0_24
Download citation
DOI: https://doi.org/10.1007/978-3-642-38750-0_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38749-4
Online ISBN: 978-3-642-38750-0
eBook Packages: Computer ScienceComputer Science (R0)