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Performance, Design, and Autotuning of Batched GEMM for GPUs,” University of Tennessee Computer Science Technical Report, no. UT-EECS-16-739: University of Tennessee, February 2016.“
Performance, Design, and Autotuning of Batched GEMM for GPUs,” The International Supercomputing Conference (ISC High Performance 2016), Frankfurt, Germany, June 2016.“
Performance, Design, and Autotuning of Batched GEMM for GPUs,” High Performance Computing: 31st International Conference, ISC High Performance 2016, Frankfurt, Germany, June 19-23, 2016, Proceedings, no. 9697: Springer International Publishing, pp. 21–38, 2016. DOI: 10.1007/978-3-319-41321-1_2“
Performance Tuning and Optimization Techniques of Fixed and Variable Size Batched Cholesky Factorization on GPUs,” International Conference on Computational Science (ICCS'16), San Diego, CA, June 2016.“
PLASMA 17 Performance Report,” Innovative Computing Laboratory Technical Report, no. ICL-UT-17-11: University of Tennessee, June 2017.“
PLASMA 17.1 Functionality Report,” Innovative Computing Laboratory Technical Report, no. ICL-UT-17-10: University of Tennessee, June 2017.“
PLASMA: Parallel Linear Algebra Software for Multicore Using OpenMP,” ACM Transactions on Mathematical Software, vol. 45, issue 2, June 2019. DOI: 10.1145/3264491“
POMPEI: Programming with OpenMP4 for Exascale Investigations,” Innovative Computing Laboratory Technical Report, no. ICL-UT-17-09: University of Tennessee, December 2017.“
Portable HPC Programming on Intel Many-Integrated-Core Hardware with MAGMA Port to Xeon Phi,” PPAM 2013, Warsaw, Poland, September 2013.“
Power-aware Computing: Measurement, Control, and Performance Analysis for Intel Xeon Phi,” 2017 IEEE High Performance Extreme Computing Conference (HPEC'17), Best Paper Finalist, Waltham, MA, IEEE, September 2017. DOI: 10.1109/HPEC.2017.8091085“
Power-Aware HPC on Intel Xeon Phi KNL Processors , Frankfurt, Germany, ISC High Performance (ISC17), Intel Booth Presentation, June 2017.
Roadmap for the Development of a Linear Algebra Library for Exascale Computing: SLATE: Software for Linear Algebra Targeting Exascale,” SLATE Working Notes, no. 1, ICL-UT-17-02: Innovative Computing Laboratory, University of Tennessee, June 2017.“
A Set of Batched Basic Linear Algebra Subprograms,” ACM Transactions on Mathematical Software, October 2020.“
The Singular Value Decomposition: Anatomy of Optimizing an Algorithm for Extreme Scale,” SIAM Review, vol. 60, issue 4, pp. 808–865, November 2018. DOI: 10.1137/17M1117732“
Small Tensor Operations on Advanced Architectures for High-Order Applications,” University of Tennessee Computer Science Technical Report, no. UT-EECS-17-749: Innovative Computing Laboratory, University of Tennessee, April 2017.“
Sparse approximations of the Schur complement for parallel algebraic hybrid solvers in 3D,” Numerical Mathematics: Theory, Methods and Applications, vol. 3, no. 3, Beijing, Golbal Science Press, pp. 64-82, 00 2010.“
A Standard for Batched BLAS Routines , Paris, France, 17th SIAM Conference on Parallel Processing for Scientific Computing (SIAM PP16), April 2016.
Tensor Contractions using Optimized Batch GEMM Routines , San Jose, CA, GPU Technology Conference (GTC), Poster, March 2018.
Three-dimensional parallel frequency-domain visco-acoustic wave modelling based on a hybrid direct/iterative solver.,” To appear in Geophysical Prospecting journal., 00 2011.“
Toward a scalable multi-GPU eigensolver via compute-intensive kernels and efficient communication,” Proceedings of the 27th ACM International Conference on Supercomputing (ICS '13), Eugene, Oregon, USA, ACM Press, June 2013. DOI: 10.1145/2464996.2465438“
Toward High Performance Divide and Conquer Eigensolver for Dense Symmetric Matrices.,” Submitted to SIAM Journal on Scientific Computing (SISC), 00 2011.“
Toward High Performance Divide and Conquer Eigensolver for Dense Symmetric Matrices,” SIAM Journal on Scientific Computing (Accepted), July 2012.“
Towards a Complexity Analysis of Sparse Hybrid Linear Solvers,” PARA 2010, Reykjavik, Iceland, June 2010.“
Towards a High-Performance Tensor Algebra Package for Accelerators , Gatlinburg, TN, moky Mountains Computational Sciences and Engineering Conference (SMC15), September 2015.
Towards Achieving Performance Portability Using Directives for Accelerators,” The International Conference for High Performance Computing, Networking, Storage and Analysis (SC'16), Third Workshop on Accelerator Programming Using Directives (WACCPD), Salt Lake City, Utah, Innovative Computing Laboratory, University of Tennessee, November 2016.“
Towards Batched Linear Solvers on Accelerated Hardware Platforms,” 8th Workshop on General Purpose Processing Using GPUs (GPGPU 8) co-located with PPOPP 2015, San Francisco, CA, ACM, February 2015.“
Unified Development for Mixed Multi-GPU and Multi-Coprocessor Environments using a Lightweight Runtime Environment,” IPDPS 2014, Phoenix, AZ, IEEE, May 2014.“
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.
Using multiple levels of parallelism to enhance the performance of domain decomposition solvers,” Parallel Computing, vol. 36, no. 5-6: Elsevier journals, pp. 285-296, 00 2010.“
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.“