Publications
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Filters: Author is Stanimire Tomov [Clear All Filters]
Novel HPC Techniques to Batch Execution of Many Variable Size BLAS Computations on GPUs,”
International Conference on Supercomputing (ICS '17), Chicago, Illinois, ACM, June 2017.
(1.04 MB)
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A Note on Auto-tuning GEMM for GPUs,”
9th International Conference on Computational Science (ICCS 2009), no. 5544-5545, Baton Rouge, LA, pp. 884-892, May 2009.
(236.02 KB)
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Non-GPU-resident Dense Symmetric Indefinite Factorization,”
Concurrency and Computation: Practice and Experience, November 2016.
“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.
(493.17 KB)
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Model-Driven One-Sided Factorizations on Multicore, Accelerated Systems,”
Supercomputing Frontiers and Innovations, vol. 1, issue 1, 2014.
(1.86 MB)
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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.
(1.24 MB)
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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.
(1.03 MB)
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Mixed-precision orthogonalization scheme and adaptive step size for CA-GMRES on GPUs,”
VECPAR 2014 (Best Paper), Eugene, OR, June 2014.
(438.54 KB)
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Mixed-precision orthogonalization process Performance on multicore CPUs with GPUs,”
2015 SIAM Conference on Applied Linear Algebra, Atlanta, GA, SIAM, October 2015.
(301.01 KB)
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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.
(2.24 MB)
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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.
(374.8 KB)
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Mixed-precision Block Gram Schmidt Orthogonalization,”
6th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Austin, TX, ACM, November 2015.
(235.69 KB)
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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.
(706.14 KB)
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MAtrix, TEnsor, and Deep-learning Optimized Routines (MATEDOR)
, Washington, DC, NSF PI Meeting, Poster, April 2018.
(2.4 MB)
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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.
(1.3 MB)
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Matrix Algebra on GPU and Multicore Architectures
, Basel, Switzerland, Workshop on GPU-enabled Numerical Libraries, Presentation, May 2011.
(49.27 MB)
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Matrices Over Runtime Systems at Exascale,”
Supercomputing '12 (poster), Salt Lake City, Utah, November 2012.
“MATEDOR: MAtrix, TEnsor, and Deep-learning Optimized Routines
, Seattle, WA, 2020 NSF Cyberinfrastructure for Sustained Scientific Innovation (CSSI) Principal Investigator Meeting, February 2020.
(2.28 MB)
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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.
(2.55 MB)
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MAGMA-sparse Interface Design Whitepaper,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-17-05, September 2017.
(1.28 MB)
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MagmaDNN: Towards High-Performance Data Analytics and Machine Learning for Data-Driven Scientific Computing,”
ISC High Performance, Frankfurt, Germany, Springer International Publishing, June 2019.
(1.37 MB)
(8.72 MB)
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MagmaDNN – High-Performance Data Analytics for Manycore GPUs and CPUs
, Knoxville, TN, 2017 Summer Research Experiences for Undergraduate (REU), Presentation, December 2017.
(5.06 MB)
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MagmaDNN: Accelerated Deep Learning Using MAGMA,”
Practice and Experience in Advanced Research Computing (PEARC ’19), Chicago, IL, ACM, July 2019.
(1.09 MB)
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MagmaDNN 0.2 High-Performance Data Analytics for Manycore GPUs and CPUs
: University of Tennessee, January 2019.
(7.84 MB)
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MAGMA Tensors and Batched Computing for Accelerating Applications on GPUs
, San Jose, CA, GPU Technology Conference (GTC17), Presentation in Session S7728, May 2017.
(11.12 MB)
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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.
“MAGMA MIC: Optimizing Linear Algebra for Intel Xeon Phi
, Frankfurt, Germany, ISC High Performance (ISC15), Intel Booth Presentation, June 2015.
(2.03 MB)
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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.
(6.4 MB)
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MAGMA - LAPACK for HPC on Heterogeneous Architectures
, Oak Ridge, TN, Titan Summit at Oak Ridge National Laboratory, Presentation, August 2011.
(20.43 MB)
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MAGMA - LAPACK for GPUs
, Atlanta, GA, Keeneland GPU Tutorial, April 2011.
(742.14 KB)
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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.
(678.86 KB)
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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.
(929.79 KB)
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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.
(4.69 MB)
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MAGMA: A Breakthrough in Solvers for Eigenvalue Problems
, San Jose, CA, GPU Technology Conference (GTC12), Presentation, May 2012.
(9.23 MB)
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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.
(943.23 KB)
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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.
(684.73 KB)
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LU Factorization for Accelerator-Based Systems,”
IEEE/ACS AICCSA 2011, Sharm-El-Sheikh, Egypt, December 2011.
(234.86 KB)
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Lossy all-to-all exchange for accelerating parallel 3-D FFTs on hybrid architectures with GPUs,”
2022 IEEE International Conference on Cluster Computing (CLUSTER), pp. 152-160, September 2022.
“Load-Balancing Sparse Matrix Vector Product Kernels on GPUs,”
ACM Transactions on Parallel Computing, vol. 7, issue 1, March 2020.
(5.67 MB)
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Linear Algebra Software for Large-Scale Accelerated Multicore Computing,”
Acta Numerica, vol. 25, pp. 1-160, May 2016.
“Linear Algebra Software for High-Performance Computing (Part 2: Software for Hardware Accelerators and Coprocessors)
, Frankfurt, Germany, ISC High Performance (ISC18), Tutorial Presentation, June 2015.
(15.41 MB)
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Linear Algebra Prepara.on for Emergent Neural Network Architectures: MAGMA, BLAS, and Batched GPU Computing
, Virtual, LAPENNA Workshop, November 2021.
(17.8 MB)
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libCEED: Fast algebra for high-order element-based discretizations,”
Journal of Open Source Software, vol. 6, no. 63, pp. 2945, 2021.
“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.
(2.14 MB)
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Keeneland: Computational Science Using Heterogeneous GPU Computing,”
Contemporary High Performance Computing: From Petascale Toward Exascale, Boca Raton, FL, Taylor and Francis, 2013.
(2.7 MB)
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Investigating the Benefit of FP16-Enabled Mixed-Precision Solvers for Symmetric Positive Definite Matrices using GPUs,”
International Conference on Computational Science (ICCS 2020), Amsterdam, Netherlands, Springer, Cham, June 2020.
(702.38 KB)
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Investigating Power Capping toward Energy-Efficient Scientific Applications,”
Concurrency Computation: Practice and Experience, vol. 2018, issue e4485, pp. 1-14, April 2018.
(1.2 MB)
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Investigating Half Precision Arithmetic to Accelerate Dense Linear System Solvers,”
ScalA17: 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Denver, CO, ACM.
(766.35 KB)
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An Introduction to the MAGMA project - Acceleration of Dense Linear Algebra
: NVIDIA Webinar, June 2010.
Interior State Computation of Nano Structures,”
PARA 2008, 9th International Workshop on State-of-the-Art in Scientific and Parallel Computing, Trondheim, Norway, May 2008.
(137.12 KB)
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