JLSE Acknowledgements

Researchers who use JLSE’s computing resources are required to acknowledge that fact in documents. The following acknowledgement is suggested:  We gratefully acknowledge the computing resources provided and operated by the Joint Laboratory for System Evaluation (JLSE) at Argonne National Laboratory.  Also, please email a copy of the published work to admins@jlse.anl.gov.


Publication List:

  • John R. Tramm, Kord S. Smith, Benoit Forget, Andrew R. Siegel, “The Random Ray Method for neutral particle transport.”, Journal of Computational Physics, Volume 342, August (2017), Pages 229-252, ISSN 0021-9991, https://doi.org/10.1016/j.jcp.2017.04.038
  • Dang, Hoang-Vu, Sangmin Seo, Abdelhalim Amer, and Pavan Balaji. “Advanced Thread Synchronization for Multithreaded MPI Implementations.”  To appear at the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, May (2017)
  • C. Perez-Monte, M. Perez, S. Rizzi, F. Piccoli, C. Luciano, “Modelling frame losses in a parallel Alternate Frame Rendering system with a Computational Best-effort Scheme.” Computers & Graphics, August (2016), http://dx.doi.org/10.1016/j.cag.2016.08.004
  • J. Tramm, G.Gunow, T. He, K. Smith, B. Forget, A. Siegel, “A task-based parallelism and vectorized approach to 3D Method of Characteristics (MOC) reactor simulation for high performance computing architectures.”Computer Physics Communications, 202, 141-150, May (2016)
  • W. Boyd, K. Yoshii and A. Siegel, “Energy Efficiency of High-Performance Computing Platforms for Neutron Transport Calculations.” Trans. of the Amer. Nucl. Soc., ANS Summer Meeting, San Antonio, TX, USA June (2015)
  • E. Jung, R. Kettimuthu, “High-Performance Serverless Data Transfer over Wide-Area Networks”. IPDPS, May (2015)
  • K. Zhang, S. Ogrenci-Memik, G. Memik, K. Yoshii, R. Sankaran, P. Beckman, “Minimizing Thermal Variation Across System Components.” IPDPS  (2015)
  • J. Tramm, K. Yoshii, A. Siegel, “Power Profiling of a Reduced Data Movement Algorithm for Neutron Cross Section Data in Monte Carlo Simulations.” Co-HPC (2014)