Understanding Performance Interference in Next-Generation HPC Systems
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Patrick M. Widener | Kurt B. Ferreira | Patrick G. Bridges | Scott Levy | Oscar H. Mondragon | P. Bridges | Oscar H. Mondragon | Scott Levy
[1] Torsten Hoefler,et al. Understanding the Effects of Communication and Coordination on Checkpointing at Scale , 2014, SC14: International Conference for High Performance Computing, Networking, Storage and Analysis.
[2] Sandia Report,et al. Improving Performance via Mini-applications , 2009 .
[3] Carlo Gaetan,et al. Smoothing Sample Extremes with Dynamic Models , 2004 .
[4] Peter A. Dinda,et al. VSched: Mixing Batch And Interactive Virtual Machines Using Periodic Real-time Scheduling , 2005, ACM/IEEE SC 2005 Conference (SC'05).
[5] Yuzhi Cai,et al. Minimum Sample Size Determination for Generalized Extreme Value Distribution , 2010, Commun. Stat. Simul. Comput..
[6] J. Filliben. The Probability Plot Correlation Coefficient Test for Normality , 1975 .
[7] Karsten Schwan,et al. PreDatA – preparatory data analytics on peta-scale machines , 2010, 2010 IEEE International Symposium on Parallel & Distributed Processing (IPDPS).
[8] Scott Pakin,et al. The Case of the Missing Supercomputer Performance: Achieving Optimal Performance on the 8, 192 Processors of ASCI Q , 2003, SC.
[9] Torsten Hoefler,et al. Exploring the effect of noise on the performance benefit of nonblocking allreduce , 2014, EuroMPI/ASIA.
[10] Kevin T. Pedretti,et al. The impact of system design parameters on application noise sensitivity , 2010, 2010 IEEE International Conference on Cluster Computing.
[11] M. E. Galassi,et al. GNU SCIENTI C LIBRARY REFERENCE MANUAL , 2005 .
[12] Francesco Pauli,et al. Penalized likelihood inference in extreme value analyses , 2001 .
[13] Torsten Hoefler,et al. Using Simulation to Evaluate the Performance of Resilience Strategies at Scale , 2013, PMBS@SC.
[14] Scott Klasky,et al. Grid-based Parallel Data Streaming Implemented for the Gyrokinetic Toroidal Code , 2003 .
[15] Björn Holmquist,et al. First moment approximations for order statistics from the extreme value distribution , 2007 .
[16] Gregory D. Peterson,et al. An Effective Execution Time Approximation Method for Parallel Computing , 2012, IEEE Transactions on Parallel and Distributed Systems.
[17] Masato Uchida. Traffic data analysis based on extreme value theory and its applications , 2004, IEEE Global Telecommunications Conference, 2004. GLOBECOM '04..
[18] Gennady Samorodnitsky,et al. Variable heavy tails in Internet traffic , 2004, Perform. Evaluation.
[19] Asser N. Tantawi,et al. Extreme scale computing: Modeling the impact of system noise in multicore clustered systems , 2010, IPDPS.
[20] Steve Plimpton,et al. Fast parallel algorithms for short-range molecular dynamics , 1993 .
[21] Eric P. Smith,et al. An Introduction to Statistical Modeling of Extreme Values , 2002, Technometrics.
[22] Peter Hall,et al. Nonparametric Analysis of Temporal Trend When Fitting Parametric Models to ExtremeValue Data , 2000 .
[23] S. Coles,et al. An Introduction to Statistical Modeling of Extreme Values , 2001 .
[24] Torsten Hoefler,et al. Netgauge: A Network Performance Measurement Framework , 2007, HPCC.
[25] A. Jenkinson. The frequency distribution of the annual maximum (or minimum) values of meteorological elements , 1955 .
[26] Torsten Hoefler,et al. Characterizing the Influence of System Noise on Large-Scale Applications by Simulation , 2010, 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis.
[27] Susan Coghlan,et al. The Influence of Operating Systems on the Performance of Collective Operations at Extreme Scale , 2006, 2006 IEEE International Conference on Cluster Computing.
[28] A. Lumsdaine,et al. LogGOPSim: simulating large-scale applications in the LogGOPS model , 2010, HPDC '10.
[29] Karsten Schwan,et al. GoldRush: Resource efficient in situ scientific data analytics using fine-grained interference aware execution , 2013, 2013 SC - International Conference for High Performance Computing, Networking, Storage and Analysis (SC).
[30] Brian Gough,et al. GNU Scientific Library Reference Manual - Third Edition , 2003 .
[31] Ayala Cohen,et al. Extreme Percentile Regression , 1996 .
[32] Feng Pan,et al. Exploring the energy-time tradeoff in MPI programs on a power-scalable cluster , 2005, 19th IEEE International Parallel and Distributed Processing Symposium.
[33] Stephen L. Olivier,et al. Early experiences with node-level power capping on the Cray XC40 platform , 2015, E2SC '15.
[34] Allen D. Malony,et al. The ghost in the machine: observing the effects of kernel operation on parallel application performance , 2007, Proceedings of the 2007 ACM/IEEE Conference on Supercomputing (SC '07).
[35] Gunnar Blom,et al. Statistical Estimates and Transformed Beta-Variables. , 1960 .
[36] Ian Karlin,et al. LULESH Programming Model and Performance Ports Overview , 2012 .
[37] Anthony C. Davison,et al. Local likelihood smoothing of sample extremes , 2000 .
[38] Irving I. Gringorten,et al. A plotting rule for extreme probability paper , 1963 .
[39] Patrick M. Widener,et al. Scheduling In-Situ Analytics in Next-Generation Applications , 2016, 2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid).
[40] David E. Bernholdt,et al. Hobbes: composition and virtualization as the foundations of an extreme-scale OS/R , 2013, ROSS '13.
[41] Michael Mascagni,et al. SPRNG: A Scalable Library for Pseudorandom Number Generation , 1999, PP.
[42] Patrick G. Bridges,et al. Quantifying Scheduling Challenges for Exascale System Software , 2015, ROSS@HPDC.
[43] Michael Lang,et al. System-Level Support for Composition of Applications , 2015, ROSS@HPDC.
[44] Ron Brightwell,et al. Characterizing application sensitivity to OS interference using kernel-level noise injection , 2008, HiPC 2008.