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Staff information

Nathan Tallent

High Performance Computing
Scientist
Pacific Northwest National Laboratory
PO Box 999
MSIN: J4-30
Richland, WA 99352
509/372-4206

Biography

PNNL web page: http://hpc.pnnl.gov/people/tallent.

PNNL Publications

2015

  • Gawande NA, JB Manzano Franco, A Tumeo, NR Tallent, DJ Kerbyson, and A Hoisie. 2015. "Power and Performance Trade-offs for Space Time Adaptive Processing." In IEEE 20th International Conference on Application-specific Systems, Architectures and Processors (ASAP 2015), July 27-29, 2015, Toronto, Canada, pp. 41-48.  IEEE, Piscataway, NJ.  doi:10.1109/ASAP.2015.7245703
  • Tallent NR, A Vishnu, H van Dam, JA Daily, DJ Kerbyson, and A Hoisie. 2015. "Diagnosing the Causes and Severity of One-sided Message Contention." In 20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP '15), February 7-11, 2015, San Francisco, California, pp. 130-139.  Association for Computing Machinery, New York, NY.  doi:10.1145/2688500.2688516
  • Venkatesh A, A Vishnu, K Hamidouche, NR Tallent, D Panda, DJ Kerbyson, and A Hoisie. 2015. "A Case for Application Oblivious Energy-Efficient MPI Runtime." In SC15 Proceedings: International Conference on High Performance Computing, Networking, Storage and Analysis, November 15-20, 2015, Austin, Texas, p. Paper No. 29.  Association of Computing Machinery (ACM), New York, NY.  doi:10.1145/2807591.2807658

2014

  • Tallent NR, and A Hoisie. 2014. "Palm: Easing the Burden of Analytical Performance Modeling." In Proceedings of the 28th International Conference on Supercomputing (ICS '14), June 10-13, 2014 Munich, Germany, pp. 221-230.  Association for Computing Machinery, New York, NY.  doi:10.1145/2597652.2597683

2013

  • Song S, NR Tallent, and A Vishnu. 2013. "Exploring Machine Learning Techniques For Dynamic Modeling on Future Exascale Systems." In Modeling & Simulation of Exascale Systems & Applications: Workshop on Modeling & Simulation of Exascale Systems & Applications, September 18-19, 2013, Seattle, Washington.  US Department of Energy, Office of Advanced Scientific Computing Research, Washington DC. 

Advanced Computing, Mathematics, and Data

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