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Unified Model for Assessing Checkpointing Protocols at Extreme-Scale,” University of Tennessee Computer Science Technical Report (also LAWN 269), no. UT-CS-12-697, June 2012.“
Unified Model for Assessing Checkpointing Protocols at Extreme-Scale,” Concurrency and Computation: Practice and Experience, November 2013. DOI: 10.1002/cpe.3173“
An Updated Set of Basic Linear Algebra Subprograms (BLAS),” ACM Transactions on Mathematical Software, vol. 28, no. 2, pp. 135-151, December 2002. DOI: 10.1145/567806.567807“
Updating Incomplete Factorization Preconditioners for Model Order Reduction,” Numerical Algorithms, vol. 73, issue 3, no. 3, pp. 611–630, February 2016. DOI: 10.1007/s11075-016-0110-2“
The use of bulk states to accelerate the band edge state calculation of a semiconductor quantum dot,” Journal of Computational Physics (submitted), January 2006.“
The Use of Bulk States to Accelerate the Band Edge State Calculation of a Semiconductor Quantum Dot,” Journal of Computational Physics, vol. 223, pp. 774-782, 00 2007.“
Users' Guide to NetSolve v1.4.1,” ICL Technical Report, no. ICL-UT-02-05, June 2002.“
Using Advanced Vector Extensions AVX-512 for MPI Reduction,” EuroMPI/USA '20: 27th European MPI Users' Group Meeting, Austin, TX, September 2020. DOI: 10.1145/3416315.3416316“
Using Advanced Vector Extensions AVX-512 for MPI Reduction (Poster) , Austin, TX, EuroMPI/USA '20: 27th European MPI Users' Group Meeting, September 2020.
Using Arm Scalable Vector Extension to Optimize Open MPI,” 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID 2020), Melbourne, Australia, IEEE/ACM, May 2020. DOI: 10.1109/CCGrid49817.2020.00-71“
Using GPU FP16 Tensor Cores Arithmetic to Accelerate Mixed-Precision Iterative Refinement Solvers and Reduce Energy Consumption,” ISC High Performance (ISC'18), Best Poster, Frankfurt, Germany, June 2018.“
Using GPU FP16 Tensor Cores Arithmetic to Accelerate Mixed-Precision Iterative Refinement Solvers and Reduce Energy Consumption , Frankfurt, Germany, ISC High Performance (ISC18), Best Poster Award, June 2018.
On Using Incremental Profiling for the Performance Analysis of Shared Memory Parallel Applications,” Proceedings of the 13th International Euro-Par Conference on Parallel Processing (Euro-Par '07), Rennes, France, Springer LNCS, January 2007.“
Using Jacobi Iterations and Blocking for Solving Sparse Triangular Systems in Incomplete Factorization Preconditioning,” Journal of Parallel and Distributed Computing, vol. 119, pp. 219–230, November 2018. DOI: 10.1016/j.jpdc.2018.04.017“
Using MAGMA with PGI Fortran,” PGI Insider, November 2010.“
Using Mixed Precision for Sparse Matrix Computations to Enhance the Performance while Achieving 64-bit Accuracy,” ACM Transactions on Mathematical Software, vol. 34, no. 4, pp. 17-22, 00 2008.“
Using PAPI for Hardware Performance Monitoring on Linux Systems,” Conference on Linux Clusters: The HPC Revolution, Urbana, Illinois, Linux Clusters Institute, June 2001.“
Using Quantized Integer in LU Factorization with Partial Pivoting (Poster) , Seattle, WA, SIAM Conference on Parallel Processing for Scientific Computing (SIAM PP20), February 2020.
Utilizing Dataflow-based Execution for Coupled Cluster Methods,” 2014 IEEE International Conference on Cluster Computing, no. ICL-UT-14-02, Madrid, Spain, IEEE, September 2014.“
Variable-Size Batched Condition Number Calculation on GPUs,” SBAC-PAD, Lyon, France, September 2018.“
Variable-Size Batched Gauss-Huard for Block-Jacobi Preconditioning,” International Conference on Computational Science (ICCS 2017), vol. 108, Zurich, Switzerland, Procedia Computer Science, pp. 1783-1792, June 2017. DOI: 10.1016/j.procs.2017.05.186“
Variable-Size Batched Gauss-Jordan Elimination for Block-Jacobi Preconditioning on Graphics Processors,” Parallel Computing, vol. 81, pp. 131-146, January 2019. DOI: 10.1016/j.parco.2017.12.006“
Variable-Size Batched LU for Small Matrices and Its Integration into Block-Jacobi Preconditioning,” 46th International Conference on Parallel Processing (ICPP), Bristol, United Kingdom, IEEE, August 2017. DOI: 10.1109/ICPP.2017.18“
The Virtual Instrument: Support for Grid-enabled Scientific Simulations,” International Journal of High Performance Computing Applications, vol. 18, no. 1, pp. 3-17, January 2004.“
The Virtual Instrument: Support for Grid-enabled Scientific Simulations,” Journal of Parallel and Distributed Computing (submitted), October 2002.“
Virtual Systolic Array for QR Decomposition,” 15th Workshop on Advances in Parallel and Distributed Computational Models, IEEE International Parallel & Distributed Processing Symposium (IPDPS 2013), Boston, MA, IEEE, May 2013. DOI: 10.1109/IPDPS.2013.119“
VisPerf: Monitoring Tool for Grid Computing,” Lecture Notes in Computer Science, vol. 2659: Springer Verlag, Heidelberg, pp. 233-243, 00 2003.“
Visualizing Execution Traces with Task Dependencies,” 2nd Workshop on Visual Performance Analysis (VPA '15), Austin, TX, ACM, November 2015.“
Weighted Block-Asynchronous Iteration on GPU-Accelerated Systems,” Tenth International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms (Best Paper), Rhodes Island, Greece, August 2012.“
Weighted Block-Asynchronous Relaxation for GPU-Accelerated Systems,” SIAM Journal on Computing (submitted), March 2012.“
Weighted Dynamic Scheduling with Many Parallelism Grains for Offloading of Numerical Workloads to Multiple Varied Accelerators,” Proceedings of the 6th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA'15), vol. No. 5, Austin, TX, ACM, November 2015.“
What it Takes to keep PAPI Instrumental for the HPC Community,” 1st Workshop on Sustainable Scientific Software (CW3S19), Collegeville, Minnesota, July 2019.“
What it Takes to keep PAPI Instrumental for the HPC Community , Collegeville, MN, The 2019 Collegeville Workshop on Sustainable Scientific Software (CW3S19), July 2019.
Is your scheduling good? How would you know? , Bordeaux, France, 14th Scheduling for Large Scale Systems Workshop, June 2019.