Mixed precision and approximate 3D FFTs: Speed for accuracy trade-off with GPU-aware MPI and run-time data compression,” ICL Technical Report, no. ICL-UT-22-04, May 2022.“
Materials fingerprinting classification,” Computer Physics Communications, pp. 108019, May Jan. DOI: 10.1016/j.cpc.2021.108019“
Mixed-Precision Algorithm for Finding Selected Eigenvalues and Eigenvectors of Symmetric and Hermitian Matrices,” ICL Technical Report, no. ICL-UT-21-05, August 2021.“
A More Portable HeFFTe: Implementing a Fallback Algorithm for Scalable Fourier Transforms,” ICL Technical Report, no. ICL-UT-21-04: University of Tennessee, August 2021.“
MAGMA Templates for Scalable Linear Algebra on Emerging Architectures,” The International Journal of High Performance Computing Applications, vol. 34, issue 6, pp. 645-658, November 2020. DOI: 10.1177/1094342020938421“
MATEDOR: MAtrix, TEnsor, and Deep-learning Optimized Routines , Seattle, WA, 2020 NSF Cyberinfrastructure for Sustained Scientific Innovation (CSSI) Principal Investigator Meeting, February 2020.
Matrix Multiplication on Batches of Small Matrices in Half and Half-Complex Precisions,” Journal of Parallel and Distributed Computing, vol. 145, pp. 188-201, November 2020. DOI: 10.1016/j.jpdc.2020.07.001“
Mixed Precision LU Factorization on GPU Tensor Cores: Reducing Data Movement and Memory Footprint,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-13: University of Tennessee, September 2020.“
Mixed-Precision Iterative Refinement using Tensor Cores on GPUs to Accelerate Solution of Linear Systems,” Proceedings of the Royal Society A, vol. 476, issue 2243, November 2020. DOI: 10.1098/rspa.2020.0110“
Mixed-Precision Solution of Linear Systems Using Accelerator-Based Computing,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-05: University of Tennessee, May 2020.“
Multiprecision Block-Jacobi for Iterative Triangular Solves,” European Conference on Parallel Processing (Euro-Par 2020): Springer, August 2020. DOI: 10.1007/978-3-030-57675-2_34“
MagmaDNN 0.2 High-Performance Data Analytics for Manycore GPUs and CPUs : University of Tennessee, January 2019. DOI: 10.13140/RG.2.2.14906.64961
MagmaDNN: Accelerated Deep Learning Using MAGMA,” Practice and Experience in Advanced Research Computing (PEARC ’19), Chicago, IL, ACM, July 2019.“
MagmaDNN: Towards High-Performance Data Analytics and Machine Learning for Data-Driven Scientific Computing,” ISC High Performance, Frankfurt, Germany, Springer International Publishing, June 2019. DOI: 10.1007/978-3-030-34356-9_37“
Massively Parallel Automated Software Tuning,” 48th International Conference on Parallel Processing (ICPP 2019), Kyoto, Japan, ACM Press, August 2019. DOI: 10.1145/3337821.3337908“
Matrix Powers Kernels for Thick-Restart Lanczos with Explicit External Deflation,” International Parallel and Distributed Processing Symposium (IPDPS), Rio de Janeiro, Brazil, IEEE, May 2019.“
MATEDOR: MAtrix, TEnsor, and Deep-learning Optimized Routines , Dallas, TX, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), Research Poster, November 2018.
MAtrix, TEnsor, and Deep-learning Optimized Routines (MATEDOR) , Washington, DC, NSF PI Meeting, Poster, April 2018. DOI: 10.6084/m9.figshare.6174143.v3
Multi-Level Checkpointing and Silent Error Detection for Linear Workflows,” Journal of Computational Science, vol. 28, pp. 398–415, September 2018.“
MAGMA Tensors and Batched Computing for Accelerating Applications on GPUs , San Jose, CA, GPU Technology Conference (GTC17), Presentation in Session S7728, May 2017.
MagmaDNN – High-Performance Data Analytics for Manycore GPUs and CPUs , Knoxville, TN, 2017 Summer Research Experiences for Undergraduate (REU), Presentation, December 2017.
MAGMA-sparse Interface Design Whitepaper,” Innovative Computing Laboratory Technical Report, no. ICL-UT-17-05, September 2017.“
MAGMA Batched: A Batched BLAS Approach for Small Matrix Factorizations and Applications on GPUs,” Innovative Computing Laboratory Technical Report, no. ICL-UT-16-02: University of Tennessee, August 2016.“
MAGMA Embedded: Towards a Dense Linear Algebra Library for Energy Efficient Extreme Computing,” 2015 IEEE High Performance Extreme Computing Conference (HPEC ’15), (Best Paper Award), Waltham, MA, IEEE, September 2015.“
MAGMA MIC: Optimizing Linear Algebra for Intel Xeon Phi , Frankfurt, Germany, ISC High Performance (ISC15), Intel Booth Presentation, June 2015.
Mixed-precision Block Gram Schmidt Orthogonalization,” 6th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Austin, TX, ACM, November 2015.“
Mixed-Precision Cholesky QR Factorization and its Case Studies on Multicore CPU with Multiple GPUs,” SIAM Journal on Scientific Computing, vol. 37, no. 3, pp. C203-C330, May 2015. DOI: DOI:10.1137/14M0973773“
Mixed-precision orthogonalization process Performance on multicore CPUs with GPUs,” 2015 SIAM Conference on Applied Linear Algebra, Atlanta, GA, SIAM, October 2015.“
Mixing LU-QR Factorization Algorithms to Design High-Performance Dense Linear Algebra Solvers,” Journal of Parallel and Distributed Computing, vol. 85, pp. 32-46, November 2015. DOI: doi:10.1016/j.jpdc.2015.06.007“
MIAMI: A Framework for Application Performance Diagnosis ,” IPASS-2014, Monterey, CA, IEEE, March 2014. DOI: 10.1109/ISPASS.2014.6844480“
Mixed-precision orthogonalization scheme and adaptive step size for CA-GMRES on GPUs,” VECPAR 2014 (Best Paper), Eugene, OR, June 2014.“
Model-Driven One-Sided Factorizations on Multicore, Accelerated Systems,” Supercomputing Frontiers and Innovations, vol. 1, issue 1, 2014. DOI: http://dx.doi.org/10.14529/jsfi1401“
A Multithreaded Communication Substrate for OpenSHMEM,” 8th International Conference on Partitioned Global Address Space Programming Models (PGAS), Eugene, OR, October 2014.“
Multi-criteria checkpointing strategies: optimizing response-time versus resource utilization,” University of Tennessee Computer Science Technical Report, no. ICL-UT-13-01, February 2013.“
Multi-criteria Checkpointing Strategies: Response-Time versus Resource Utilization,” Euro-Par 2013, Aachen, Germany, Springer, August 2013.“
Multithreading in the PLASMA Library,” Multi and Many-Core Processing: Architecture, Programming, Algorithms, & Applications: Taylor & Francis, 00 2013.“
MAGMA: A Breakthrough in Solvers for Eigenvalue Problems , San Jose, CA, GPU Technology Conference (GTC12), Presentation, May 2012.
MAGMA: A New Generation of Linear Algebra Library for GPU and Multicore Architectures , Salt Lake City, UT, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC12), Presentation, November 2012.
MAGMA MIC: Linear Algebra Library for Intel Xeon Phi Coprocessors , Salt Lake City, UT, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC12), November 2012.
MAGMA Tutorial , Atlanta, GA, Keeneland Workshop, February 2012.
Matrices Over Runtime Systems at Exascale,” Supercomputing '12 (poster), Salt Lake City, Utah, November 2012.“
MAGMA - LAPACK for GPUs , Atlanta, GA, Keeneland GPU Tutorial, April 2011.
MAGMA - LAPACK for HPC on Heterogeneous Architectures , Oak Ridge, TN, Titan Summit at Oak Ridge National Laboratory, Presentation, August 2011.
Matrix Algebra on GPU and Multicore Architectures , Basel, Switzerland, Workshop on GPU-enabled Numerical Libraries, Presentation, May 2011.
MaPHyS or the Development of a Parallel Algebraic Domain Decomposition Solver in the Course of the Solstice Project,” Sparse Days 2010 Meeting at CERFACS, Toulouse, France, June 2010.“
Mixed-Tool Performance Analysis on Hybrid Multicore Architectures,” First International Workshop on Parallel Software Tools and Tool Infrastructures (PSTI 2010), San Diego, CA, September 2010.“
Making Performance Analysis and Tuning Part of the Software Development Cycle,” Proceedings of DoD HPCMP UGC 2009, San Diego, CA, IEEE, June 2009.“
Modeling the Office of Science Ten Year Facilities Plan: The PERI Architecture Tiger Team,” SciDAC 2009, Journal of Physics: Conference Series, vol. 180(2009)012039, San Diego, California, IOP Publishing, July 2009.“
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.“