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Improving scalability and reliability of MPI-agnostic transparent checkpointing for production workloads at NERSC [article]

Prashant Singh Chouhan
2021 arXiv   pre-print
In this talk, we present ongoing work at NERSC to enable MANA for NERSC's production workloads, including fixing bugs that were exposed by the top applications at NERSC, adding new features to address  ...  It is therefore vital to get transparent C/R capability working at NERSC.  ...  ACKNOWLEDGEMENT The authors would like to thank Steve Leak and Chris Samuel at NERSC for valuable discussions and help.  ... 
arXiv:2103.08546v2 fatcat:u4fop5dq6beiplzamvdq4dqpxm

NWChem: Past, Present, and Future [article]

E. Aprà and E. J. Bylaska and W. A. de Jong and N. Govind and K. Kowalski and T. P. Straatsma and M. Valiev and H. J. J. van Dam and Y. Alexeev and J. Anchell and V. Anisimov and F. W. Aquino and R. Atta-Fynn and J. Autschbach and N. P. Bauman and J. C. Becca and D. E. Bernholdt and K. Bhaskaran-Nair and S. Bogatko and P. Borowski and J. Boschen and J. Brabec and A. Bruner and E. Cauët and Y. Chen and G. N. Chuev and C. J. Cramer and J. Daily and M. J. O. Deegan and T. H. Dunning Jr. and M. Dupuis and K. G. Dyall and G. I. Fann and S. A. Fischer and A. Fonari and H. Früuchtl and L. Gagliardi and J. Garza and N. Gawande and S. Ghosh and K. Glaesemann and A. W. Götz and J. Hammond and V. Helms and E. D. Hermes and K. Hirao and S. Hirata and M. Jacquelin and L. Jensen and B. G. Johnson and H. Jónsson and R. A. Kendall and M. Klemm and R. Kobayashi and V. Konkov and S. Krishnamoorthy and M. Krishnan and Z. Lin and R. D. Lins and R. J. Littlefield and A. J. Logsdail and K. Lopata and W. Ma and A. V. Marenich and J. Martin del Campo and D. Mejia-Rodriguez and J. E. Moore and J. M. Mullin and T. Nakajima and D. R. Nascimento and J. A. Nichols and P. J. Nichols and J. Nieplocha and A. Otero de la Roza and B. Palmer and A. Panyala and T. Pirojsirikul and B. Peng and R. Peverati and J. Pittner and L. Pollack and R. M. Richard and P. Sadayappan and G. C. Schatz and W.A. Shelton and D. W. Silverstein and D. M. A. Smith and T. A. Soares and D. Song and M. Swart and H. L. Taylor and G. S. Thomas and V. Tipparaju and D. G. Truhlar and K. Tsemekhman and T. Van Voorhis and Á. Vázquez-Mayagoitia and P. Verma and O. Villa and A. Vishnu and K. D. Vogiatzis and D. Wang and J. H. Weare and M. J. Williamson and T. L. Windus and K. Woliński and A. T. Wong and Q. Wu and C. Yang and Q. Yu and M. Zacharias and Z. Zhang and Y. Zhao and R. J. Harrison
2020 Journal of Chemical Physics   accepted
and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory.  ...  of atomistic and electronic properties.  ...  Kendall, Jarek Nieplocha, and Daniel W. Silverstein.  ... 
doi:10.1063/5.0004997 pmid:32414274 arXiv:2004.12023v2 fatcat:zzz2vczvkjbnjmqz2ssvd6ouku

Preparing NERSC users for Cori, a Cray XC40 system with Intel many integrated cores

Yun He, Brandon Cook, Jack Deslippe, Brian Friesen, Richard Gerber, Rebecca Hartman-Baker, Alice Koniges, Thorsten Kurth, Stephen Leak, Woo-Sun Yang, Zhengji Zhao, Eddie Baron (+1 others)
2017 Concurrency and Computation  
System usage data, job completion analysis, programming and running jobs issues, and a few successful user stories on KNL are presented.  ...  The NERSC Exascale Science Applications Program (NESAP), 5 in which code teams were connected to experts at NERSC, Intel, and Cray, was developed to help enable a significant fraction of the NERSC workload  ...  ACKNOWLEDGMENTS We would like to thank Cray teams (onsite and remote staff), Intel teams (training and dungeon session staff), and also our NERSC colleagues (especially CSG, ATG, DAS staff, and NESAP postdocs  ... 
doi:10.1002/cpe.4291 fatcat:irtqvi5fajbs5dnztqxxgj5c4i

Towards understanding HPC users and systems: A NERSC case study

Gonzalo P. Rodrigo, P.-O. Östberg, Erik Elmroth, Katie Antypas, Richard Gerber, Lavanya Ramakrishnan
2018 Journal of Parallel and Distributed Computing  
We apply this methodology to the workloads of three systems (Hopper, Edison, and Carver) at the National Energy Research Scientific Computing Center (NERSC).  ...  In this paper, we present a methodology to characterize workloads and assess their heterogeneity, at a particular time period and its evolution over time.  ...  Our results and methodology provide a strong foundation for future scheduling research and systems operations management. Scheduling research needs to address present and future workloads.  ... 
doi:10.1016/j.jpdc.2017.09.002 fatcat:rqdaahtly5hc5jmjltxl35vrcq

Analysis of Cray XC30 Performance Using Trinity-NERSC-8 Benchmarks and Comparison with Cray XE6 and IBM BG/Q [chapter]

M. J. Cordery, Brian Austin, H. J. Wassermann, C. S. Daley, N. J. Wright, S. D. Hammond, D. Doerfler
2014 Lecture Notes in Computer Science  
Strong scaling results are presented, using both MPI-only and MPI+OpenMP execution models.  ...  processors; and Mira, an IBM BlueGene/Q with PowerPC A2 processors.  ...  To this end, we present results showing how each benchmark strong scales on three different architectures: Edison, a state-of-the art Cray XC30 at NERSC; Hopper, a Cray XE6 (also at NERSC); and Mira and  ... 
doi:10.1007/978-3-319-10214-6_3 fatcat:vdsw33ihejhgne4okhtbra5si4

I/O performance of virtualized cloud environments

Devarshi Ghoshal, Richard Shane Canon, Lavanya Ramakrishnan
2011 Proceedings of the second international workshop on Data intensive computing in the clouds - DataCloud-SC '11  
This paper will present our results in benchmarking the I/O performance over different cloud and HPC platforms to identify the major bottlenecks in existing infrastructure.  ...  Our results highlight the overhead and variability in I/O performance on both public and private cloud solutions.  ...  Multinode MPI Results I/O Operations The local disk on the instance performs better than the EBS volumes on the VMs at NERSC.  ... 
doi:10.1145/2087522.2087535 fatcat:56sccsweynca5h3ducxi6o33uy

Accelerating Spectroscopic Data Processing Using Python and GPUs on NERSC Supercomputers

Daniel Margala, Laurie Stephey, Rollin Thomas, Stephen Bailey
2021 Proceedings of the 20th Python in Science Conference   unpublished
The new Perlmutter supercomputer system at the National Energy Scientific Research and Computing Center (NERSC) will feature over 6,000 NVIDIA A100 GPUs across 1,500 nodes.  ...  NERSC.  ...  at NERSC.  ... 
doi:10.25080/majora-1b6fd038-004 fatcat:bdh3bggogncfdn32azbq27k7vq

Grid -Based Parallel Data Streaming implemented for the Gyrokinetic Toroidal Code

S. Klasky, S. Ethier, Z. Lin, K. Martins, D. McCune, R. Samtaney
2003 Proceedings of the 2003 ACM/IEEE conference on Supercomputing - SC '03  
The present approach is conducive to using the grid to pipeline the simulation with post-processing and visualization.  ...  Data transfer experiments show that this concurrent data transfer approach is more favorable compared with writing to local disk and then transferring this data to be post-processed.  ...  One of our future goals is to stream data across from one of our largest simulations at NERSC, Run9 shown in Table 2 .  ... 
doi:10.1145/1048935.1050175 dblp:conf/sc/KlaskyELMMS03 fatcat:2kz3rp2ctzc6nlmusnv6ojlvhq

A Programming Model Performance Study Using the NAS Parallel Benchmarks

Hongzhang Shan, Filip Blagojević, Seung-Jai Min, Paul Hargrove, Haoqiang Jin, Karl Fuerlinger, Alice Koniges, Nicholas J. Wright
2010 Scientific Programming  
In this paper we use the NAS Parallel Benchmarks to study three programming models, MPI, OpenMP and PGAS to understand their performance and memory usage characteristics on current multicore architectures  ...  Harnessing the power of multicore platforms is challenging due to the additional levels of parallelism present.  ...  Conclusions In this paper we have examined the performance of three different programming models OpenMP, MPI and UPC on the Cray XT5 machine, Hopper at NERSC, and the Linux InfiniBand cluster Ranger at  ... 
doi:10.1155/2010/715637 fatcat:spirchvsenf4tmfv2sdc5aehe4

Managing Variability in the IO Performance of Petascale Storage Systems

Jay Lofstead, Fang Zheng, Qing Liu, Scott Klasky, Ron Oldfield, Todd Kordenbrock, Karsten Schwan, Matthew Wolf
2010 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis  
This paper presents interference effects measurements for two different file systems at multiple supercomputing sites.  ...  usage environment and with artificially introduced levels of 'noise'.  ...  from the Department of Defense, a grant from the Office of Science through the SciDAC program, and the SDM center in the OSCR office.  ... 
doi:10.1109/sc.2010.32 dblp:conf/sc/LofsteadZLKOKSW10 fatcat:huk6vw7fdvei3ghbm7z5gu42g4

Near real-time streaming analysis of big fusion data [article]

Ralph Kube and R. Michael Churchill and CS Chang and Jong Choi and Jason Wang and Scott Klasky and Laurie Stephey and Minjun Choi and Eli Dart
2021 arXiv   pre-print
Our focus is on the streaming analysis of ECEi data measured at KSTAR on NERSCs supercomputers and we routinely achieve data transfer rates of about 500 Megabyte per second.  ...  This article describe the modular and expandable software architecture of DELTA and presents performance benchmarks of its individual components as well as of entire workflows.  ...  Acknowledgement(s) This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S.  ... 
arXiv:2108.08896v1 fatcat:f4yzgole7vbmjhooz4vlsxydie

Simulation of vector boson plus many jet final states at the high luminosity LHC [article]

Stefan Höche, Stefan Prestel, Holger Schulz
2019 arXiv   pre-print
We present a novel event generation framework for the efficient simulation of vector boson plus multi-jet backgrounds at the high-luminosity LHC and at possible future hadron colliders.  ...  MPI parallelization of parton-level and particle-level event generation and storage of parton-level event information using the HDF5 data format allow us to obtain leading-order merged Monte-Carlo predictions  ...  "HPC framework for event generation at colliders"  ... 
arXiv:1905.05120v1 fatcat:3q5gmbbj45fyxni265up4y2wrm

Power efficiency in high performance computing

Shoaib Kamil, John Shalf, Erich Strohmaier
2008 Proceedings, International Parallel and Distributed Processing Symposium (IPDPS)  
Furthermore, we show through measurements on a large scale system that the power consumed by smaller subsets of the system can be projected straightforwardly and accurately to estimate the power consumption  ...  and in the future.  ...  The relative power usage at peak is only 19% more than at idle. Lastly, we present the power usage of our PowerMac G5 in Figure 3 .  ... 
doi:10.1109/ipdps.2008.4536223 dblp:conf/ipps/KamilSS08 fatcat:x2tfqis7cffi5dhklt7rct46ju

HDF5 as a vehicle for in transit data movement

Junmin Gu, Burlen Loring, Kesheng Wu, E. Wes Bethel
2019 Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization - ISAV '19  
a transport that uses slower layers of the storage hierarchy, such as an NVRAM-based persistent storage presented as a distributed file system.  ...  For in transit use cases at scale on HPC platforms, one might expect that an in transit data transport mechanism that uses faster layers of the storage hierarchy, such as DRAM memory, would always outperform  ...  All the data used for this paper is collected on the KNL nodes from the Cori system at NERSC.  ... 
doi:10.1145/3364228.3364237 dblp:conf/sc/GuLWB19 fatcat:x4inwfcuhjahhi32xsncqbpevm

On the use of burst buffers for accelerating data-intensive scientific workflows

Rafael Ferreira da Silva, Scott Callaghan, Ewa Deelman
2017 Proceedings of the 12th Workshop on Workflows in Support of Large-Scale Science - WORKS '17  
In this paper, we examine the impact of burst buffers through the remote-shared, allocatable burst buffers on the Cori system at NERSC.  ...  up with compute and memory performance.  ...  for burst buffer usage.  ... 
doi:10.1145/3150994.3151000 dblp:conf/sc/SilvaCD17 fatcat:tomvvnfqgnbdlbjyl67x4u7z5y
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