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PAPI: Counting outside the Box , Barcelona, Spain, 8th JLESC Meeting, April 2018.
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BlackjackBench: Portable Hardware Characterization with Automated Results Analysis,” The Computer Journal, March 2013. DOI: 10.1093/comjnl/bxt057“
Software-Defined Events through PAPI for In-Depth Analysis of Application Performance , Basel, Switzerland, 5th Platform for Advanced Scientific Computing Conference (PASC18), July 2018.
Software-Defined Events through PAPI,” 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Rio de Janeiro, Brazil, IEEE, May 2019. DOI: 10.1109/IPDPSW.2019.00069“
Does your tool support PAPI SDEs yet? , Tahoe City, CA, 13th Scalable Tools Workshop, July 2019.
MPI-aware Compiler Optimizations for Improving Communication-Computation Overlap,” Proceedings of the 23rd annual International Conference on Supercomputing (ICS '09), Yorktown Heights, NY, USA, ACM, pp. 316-325, June 2009.“
PAPI's new Software-Defined Events for in-depth Performance Analysis , Dresden, Germany, 13th Parallel Tools Workshop, September 2019.
Understanding Native Event Semantics , Knoxville, TN, 9th JLESC Workshop, April 2019.
PaRSEC in Practice: Optimizing a Legacy Chemistry Application through Distributed Task-Based Execution,” 2015 IEEE International Conference on Cluster Computing, Chicago, IL, IEEE, September 2015.“
From Serial Loops to Parallel Execution on Distributed Systems,” PPoPP 2012 (submitted), New Orleans, LA, February 2012.“
PTG: An Abstraction for Unhindered Parallelism,” International Workshop on Domain-Specific Languages and High-Level Frameworks for High Performance Computing (WOLFHPC), New Orleans, LA, IEEE Press, November 2014.“
Is your scheduling good? How would you know? , Bordeaux, France, 14th Scheduling for Large Scale Systems Workshop, June 2019.
Characterization of Power Usage and Performance in Data-Intensive Applications using MapReduce over MPI,” 2019 International Conference on Parallel Computing (ParCo2019), Prague, Czech Republic, September 2019.“
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Accelerating Time-To-Solution for Computational Science and Engineering,” SciDAC Review, 00 2009.“
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FT-MPI, Fault-Tolerant Metacomputing and Generic Name Services: A Case Study,” Lecture Notes in Computer Science, vol. 4192, no. ICL-UT-06-14: Springer Berlin / Heidelberg, pp. 133-140, 00 2006.“
Dynamically balanced synchronization-avoiding LU factorization with multicore and GPUs,” University of Tennessee Computer Science Technical Report, no. ut-cs-13-713, July 2013.“
On Algorithmic Variants of Parallel Gaussian Elimination: Comparison of Implementations in Terms of Performance and Numerical Properties,” University of Tennessee Computer Science Technical Report, no. UT-CS-13-715, July 2013, 2012.“
Performance evaluation of LU factorization through hardware counter measurements,” University of Tennessee Computer Science Technical Report, no. ut-cs-12-700, October 2012.“
Dynamically balanced synchronization-avoiding LU factorization with multicore and GPUs,” Fourth International Workshop on Accelerators and Hybrid Exascale Systems (AsHES), IPDPS 2014, May 2014.“
A Survey of Recent Developments in Parallel Implementations of Gaussian Elimination,” Concurrency and Computation: Practice and Experience, vol. 27, issue 5, pp. 1292-1309, April 2015. DOI: 10.1002/cpe.3306“
Acceleration of the BLAST Hydro Code on GPU,” Supercomputing '12 (poster), Salt Lake City, Utah, SC12, November 2012.“
Optimizing the SVD Bidiagonalization Process for a Batch of Small Matrices,” International Conference on Computational Science (ICCS 2017), Zurich, Switzerland, Procedia Computer Science, June 2017.“
LU Factorization of Small Matrices: Accelerating Batched DGETRF on the GPU,” 16th IEEE International Conference on High Performance Computing and Communications (HPCC), Paris, France, IEEE, August 2014.“
A Step towards Energy Efficient Computing: Redesigning A Hydrodynamic Application on CPU-GPU,” IPDPS 2014, Phoenix, AZ, IEEE, May 2014.“
Accelerating the SVD Bi-Diagonalization of a Batch of Small Matrices using GPUs,” Journal of Computational Science, vol. 26, pp. 237–245, May 2018. DOI: 10.1016/j.jocs.2018.01.007“
A Fast Batched Cholesky Factorization on a GPU,” International Conference on Parallel Processing (ICPP-2014), Minneapolis, MN, September 2014.“
Hydrodynamic Computation with Hybrid Programming on CPU-GPU Clusters,” University of Tennessee Computer Science Technical Report, no. ut-cs-13-714, July 2013.“
Hierarchical QR Factorization Algorithms for Multi-Core Cluster Systems,” University of Tennessee Computer Science Technical Report (also Lawn 257), no. UT-CS-11-684, October 2011.“
Remembering Ken Kennedy,” SciDAC Review, vol. 5, no. 2007, 00 2007.“
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Autotuning Numerical Dense Linear Algebra for Batched Computation With GPU Hardware Accelerators,” Proceedings of the IEEE, vol. 106, issue 11, pp. 2040–2055, November 2018. DOI: 10.1109/JPROC.2018.2868961“
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Report on the Sunway TaihuLight System,” University of Tennessee Computer Science Technical Report, no. UT-EECS-16-742: University of Tennessee, June 2016.“
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Biannual Top-500 Computer Lists Track Changing Environments for Scientific Computing,” SIAM News, vol. 34, no. 9, October 2002.“
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Self Adapting Numerical Algorithm for Next Generation Applications,” International Journal of High Performance Computing Applications, vol. 17, no. 2, pp. 125-132, January 2003.“
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