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Kernel-assisted and topology-aware MPI collective communications on multi-core/many-core platforms,” Journal of Parallel and Distributed Computing, vol. 73, issue 7, pp. 1000-1010, July 2013. DOI: 10.1016/j.jpdc.2013.01.015“
L2 Cache Modeling for Scientific Applications on Chip Multi-Processors,” Proceedings of the 2007 International Conference on Parallel Processing, Xi'an, China, IEEE Computer Society, January 2007.“
LAPACK,” Handbook of Linear Algebra, Second, Boca Raton, FL, CRC Press, 2013.“
LAPACK 2005 Prospectus: Reliable and Scalable Software for Linear Algebra Computations on High End Computers : LAPACK Working Note 164, January 2005.
LAPACK for Clusters Project: An Example of Self Adapting Numerical Software,” Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS 04'), vol. 9, Big Island, Hawaii, pp. 90282, January 2004.“
LAPACK Users' Guide, 3rd ed.,” Philadelphia: Society for Industrial and Applied Mathematics, January 1999.“
LAWN 294: Aasen's Symmetric Indenite Linear Solvers in LAPACK,” LAPACK Working Note, no. LAWN 294, ICL-UT-17-13: University of Tennessee, December 2017.“
Leading Edge Hybrid Multi-GPU Algorithms for Generalized Eigenproblems in Electronic Structure Calculations,” International Supercomputing Conference (ISC), Lecture Notes in Computer Science, vol. 7905, Leipzig, Germany, Springer Berlin Heidelberg, pp. 67-80, June 2013. DOI: 10.1007/978-3-642-38750-0_6“
Least Squares Performance Report,” SLATE Working Notes, no. 9, ICL-UT-18-10: Innovative Computing Laboratory, University of Tennessee, December 2018.“
Least Squares Solvers for Distributed-Memory Machines with GPU Accelerators,” ACM International Conference on Supercomputing (ICS '19), Phoenix, Arizona, ACM, pp. 117–126, June 2019. DOI: https://dl.acm.org/doi/abs/10.1145/3330345.3330356“
Level-3 Cholesky Factorization Routines Improve Performance of Many Cholesky Algorithms,” ACM Transactions on Mathematical Software (TOMS), vol. 39, issue 2, February 2013. DOI: 10.1145/2427023.2427026“
Level-3 Cholesky Kernel Subroutine of a Fully Portable High Performance Minimal Storage Hybrid Format Cholesky Algorithm,” ACM TOMS (submitted), also LAPACK Working Note (LAWN) 211, 00 2010.“
Leveraging PaRSEC Runtime Support to Tackle Challenging 3D Data-Sparse Matrix Problems,” 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2021), Portland, OR, IEEE, May 2021.“
Limitations of the Playstation 3 for High Performance Cluster Computing,” University of Tennessee Computer Science Technical Report, UT-CS-07-597 (Also LAPACK Working Note 185), 00 2007.“
Linear Algebra Software for Large-Scale Accelerated Multicore Computing,” Acta Numerica, vol. 25, pp. 1-160, May 2016. DOI: 10.1017/S0962492916000015“
Linear Systems Performance Report,” SLATE Working Notes, no. 8, ICL-UT-18-08: Innovative Computing Laboratory, University of Tennessee, September 2018.“
Linear Systems Solvers for Distributed-Memory Machines with GPU Accelerators,” Euro-Par 2019: Parallel Processing, vol. 11725: Springer, pp. 495–506, August 2019. DOI: 10.1007/978-3-030-29400-7_35“
The LINPACK Benchmark: Past, Present, and Future,” Concurrency: Practice and Experience, vol. 15, pp. 803-820, 00 2008.“
LINPACK on Future Manycore and GPu Based Systems,” PARA 2010, Reykjavik, Iceland, June 2010.“
Load-Balancing Sparse Matrix Vector Product Kernels on GPUs,” ACM Transactions on Parallel Computing, vol. 7, issue 1, March 2020. DOI: 10.1145/3380930“
Locality and Topology aware Intra-node Communication Among Multicore CPUs,” Proceedings of the 17th EuroMPI conference, Stuttgart, Germany, LNCS, September 2010.“
Logistical Computing and Internetworking: Middleware for the Use of Storage in Communication,” submitted to SC2001, Denver, Colorado, November 2001.“
Logistical Quality of Service in NetSolve,” Computer Communications, vol. 22, no. 11, pp. 1034-1044, January 1999.“
A Look Back on 30 Years of the Gordon Bell Prize,” International Journal of High Performance Computing and Networking, vol. 31, issue 6, pp. 469–484, 2017.“
Looking Back at Dense Linear Algebra Software,” Journal of Parallel and Distributed Computing, vol. 74, issue 7, pp. 2548–2560, July 2014. DOI: 10.1016/j.jpdc.2013.10.005“
Looking Back at Dense Linear Algebra Software,” Perspectives on Parallel and Distributed Processing: Looking Back and What's Ahead (to appear), 00 2012.“
LU Factorization for Accelerator-Based Systems,” IEEE/ACS AICCSA 2011, Sharm-El-Sheikh, Egypt, December 2011.“
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.“
LU Factorization with Partial Pivoting for a Multicore System with Accelerators,” IEEE Transactions on Parallel and Distributed Computing, vol. 24, issue 8, pp. 1613-1621, August 2013. DOI: http://doi.ieeecomputersociety.org/10.1109/TPDS.2012.242“
LU, QR, and Cholesky Factorizations: Programming Model, Performance Analysis and Optimization Techniques for the Intel Knights Landing Xeon Phi,” IEEE High Performance Extreme Computing Conference (HPEC'16), Waltham, MA, IEEE, September 2016.“
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 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 - LAPACK for HPC on Heterogeneous Architectures , Oak Ridge, TN, Titan Summit at Oak Ridge National Laboratory, Presentation, August 2011.
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 MIC: Optimizing Linear Algebra for Intel Xeon Phi , Frankfurt, Germany, ISC High Performance (ISC15), Intel Booth Presentation, June 2015.
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“
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 – High-Performance Data Analytics for Manycore GPUs and CPUs , Knoxville, TN, 2017 Summer Research Experiences for Undergraduate (REU), Presentation, December 2017.
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“
MAGMA-sparse Interface Design Whitepaper,” Innovative Computing Laboratory Technical Report, no. ICL-UT-17-05, September 2017.“
The Marketplace for High-Performance Computers,” Parallel Computing, vol. 25, no. 13-14, pp. 1517-1545, October 2002.“
Massively Parallel Automated Software Tuning,” 48th International Conference on Parallel Processing (ICPP 2019), Kyoto, Japan, ACM Press, August 2019. DOI: 10.1145/3337821.3337908“
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.
Matrices Over Runtime Systems at Exascale,” Supercomputing '12 (poster), Salt Lake City, Utah, November 2012.“
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“
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.“
Matrix Product on Heterogeneous Master Worker Platforms,” 2008 PPoPP Conference, Salt Lake City, Utah, January 2008.“
MAtrix, TEnsor, and Deep-learning Optimized Routines (MATEDOR) , Washington, DC, NSF PI Meeting, Poster, April 2018. DOI: 10.6084/m9.figshare.6174143.v3
Measuring Computer Performance: A Practioner's Guide,” SIAM Review (book review), vol. 43, no. 2, pp. 383-384, 00 2001.“