Publications
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
(7.84 MB)

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
(1.37 MB)
(8.72 MB)
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Massively Parallel Automated Software Tuning,”
48th International Conference on Parallel Processing (ICPP 2019), Kyoto, Japan, ACM Press, August 2019.
DOI: 10.1145/3337821.3337908
(911.88 KB)
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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.
(480.73 KB)
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Optimizing Batch HGEMM on Small Sizes Using Tensor Cores
, San Jose, CA, GPU Technology Conference (GTC), March 2019.
(2.47 MB)

PAPI Software-Defined Events for in-Depth Performance Analysis,”
The International Journal of High Performance Computing Applications, vol. 33, issue 6, pp. 1113-1127, November 2019.
(442.39 KB)
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PAPI's new Software-Defined Events for in-depth Performance Analysis
, Dresden, Germany, 13th Parallel Tools Workshop, September 2019.
(3.14 MB)

ParILUT – A Parallel Threshold ILU for GPUs,”
IEEE International Parallel and Distributed Processing Symposium (IPDPS), Rio de Janeiro, Brazil, IEEE, May 2019.
DOI: 10.1109/IPDPS.2019.00033
(505.95 KB)
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Performance Analysis of Tile Low-Rank Cholesky Factorization Using PaRSEC Instrumentation Tools,”
Workshop on Programming and Performance Visualization Tools (ProTools 19) at SC19, Denver, CO, ACM, November 2019.
(429.55 KB)
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Performance of Asynchronous Optimized Schwarz with One-sided Communication,”
Parallel Computing, vol. 86, pp. 66-81, August 2019.
DOI: 10.1016/j.parco.2019.05.004
(3.09 MB)
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PLASMA: Parallel Linear Algebra Software for Multicore Using OpenMP,”
ACM Transactions on Mathematical Software, vol. 45, issue 2, June 2019.
DOI: 10.1145/3264491
(7.5 MB)
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Progressive Optimization of Batched LU Factorization on GPUs,”
IEEE High Performance Extreme Computing Conference (HPEC’19), Waltham, MA, IEEE, September 2019.
(299.38 KB)
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Race to Exascale,”
Computing in Science and Engineering, vol. 21, issue 1, pp. 4-5, March 2019.
DOI: 10.1109/MCSE.2018.2882574
(106.97 KB)
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SLATE: Design of a Modern Distributed and Accelerated Linear Algebra Library
, Denver, CO, International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), November 2019.
(16.19 MB)

SLATE: Design of a Modern Distributed and Accelerated Linear Algebra Library,”
International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), Denver, CO, ACM, November 2019.
DOI: 10.1145/3295500.3356223
(2.01 MB)
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SLATE Developers' Guide,”
SLATE Working Notes, no. 11, ICL-UT-19-02: Innovative Computing Laboratory, University of Tennessee, December 2019.
(1.68 MB)
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SLATE Mixed Precision Performance Report,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-19-03: University of Tennessee, April 2019.
(1.04 MB)
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SLATE Working Note 12: Implementing Matrix Inversions,”
SLATE Working Notes, no. 12, ICL-UT-19-04: Innovative Computing Laboratory, University of Tennessee, June 2019.
(1.95 MB)
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SLATE Working Note 13: Implementing Singular Value and Symmetric/Hermitian Eigenvalue Solvers,”
SLATE Working Notes, no. 13, ICL-UT-19-07: Innovative Computing Laboratory, University of Tennessee, September 2019.
(3.16 MB)
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Software-Defined Events through PAPI,”
2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Rio de Janeiro, Brazil, IEEE, May 2019.
DOI: 10.1109/IPDPSW.2019.00069
(446.41 KB)
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Solving Linear Diophantine Systems on Parallel Architectures,”
IEEE Transactions on Parallel and Distributed Systems, vol. 30, issue 5, pp. 1158-1169, May 2019.
DOI: http://dx.doi.org/10.1109/TPDS.2018.2873354
(802.97 KB)
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Towards Continuous Benchmarking,”
Platform for Advanced Scientific Computing Conference (PASC 2019), Zurich, Switzerland, ACM Press, June 2019.
DOI: 10.1145/3324989.3325719
(1.51 MB)
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Towards Half-Precision Computation for Complex Matrices: A Case Study for Mixed Precision Solvers on GPUs,”
ScalA19: 10th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Denver, CO, IEEE, November 2019.
(523.87 KB)
(3.42 MB)
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Understanding Native Event Semantics
, Knoxville, TN, 9th JLESC Workshop, April 2019.
(2.33 MB)

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
(1.9 MB)
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What it Takes to keep PAPI Instrumental for the HPC Community,”
1st Workshop on Sustainable Scientific Software (CW3S19), Collegeville, Minnesota, July 2019.
(50.57 KB)
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What it Takes to keep PAPI Instrumental for the HPC Community
, Collegeville, MN, The 2019 Collegeville Workshop on Sustainable Scientific Software (CW3S19), July 2019.
(3.29 MB)

Is your scheduling good? How would you know?
, Bordeaux, France, 14th Scheduling for Large Scale Systems Workshop, June 2019.
(2.5 MB)

The 30th Anniversary of the Supercomputing Conference: Bringing the Future Closer—Supercomputing History and the Immortality of Now,”
Computer, vol. 51, issue 10, pp. 74–85, November 2018.
DOI: 10.1109/MC.2018.3971352
(1.73 MB)
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Accelerating NWChem Coupled Cluster through dataflow-based Execution,”
The International Journal of High Performance Computing Applications, vol. 32, issue 4, pp. 540--551, July 2018.
DOI: 10.1177/1094342016672543
(1.68 MB)
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Accelerating the SVD Bi-Diagonalization of a Batch of Small Matrices using GPUs,”
Journal of Computational Science, vol. 26, pp. 237–245, May 2018.
DOI: 10.1016/j.jocs.2018.01.007
(2.18 MB)
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Accelerating the SVD Two Stage Bidiagonal Reduction and Divide and Conquer Using GPUs,”
Parallel Computing, vol. 74, pp. 3–18, May 2018.
DOI: 10.1016/j.parco.2017.10.004
(1.34 MB)
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ADAPT: An Event-Based Adaptive Collective Communication Framework,”
The 27th International Symposium on High-Performance Parallel and Distributed Computing (HPDC '18), Tempe, Arizona, ACM Press, June 2018.
DOI: 10.1145/3208040.3208054
(493.65 KB)
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Algorithms and Optimization Techniques for High-Performance Matrix-Matrix Multiplications of Very Small Matrices,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-18-09: Innovative Computing Laboratory, University of Tennessee, September 2018.
(3.74 MB)
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Analysis and Design Techniques towards High-Performance and Energy-Efficient Dense Linear Solvers on GPUs,”
IEEE Transactions on Parallel and Distributed Systems, vol. 29, issue 12, pp. 2700–2712, December 2018.
DOI: 10.1109/TPDS.2018.2842785
(2.53 MB)
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Analyzing Performance of BiCGStab with Hierarchical Matrix on GPU Clusters,”
IEEE International Parallel and Distributed Processing Symposium (IPDPS), Vancouver, BC, Canada, IEEE, May 2018.
(1.37 MB)
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Autotuning in High-Performance Computing Applications,”
Proceedings of the IEEE, vol. 106, issue 11, pp. 2068–2083, November 2018.
DOI: 10.1109/JPROC.2018.2841200
(2.5 MB)
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Autotuning Numerical Dense Linear Algebra for Batched Computation With GPU Hardware Accelerators,”
Proceedings of the IEEE, vol. 106, issue 11, pp. 2040–2055, November 2018.
DOI: 10.1109/JPROC.2018.2868961
(2.53 MB)
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Autotuning Techniques for Performance-Portable Point Set Registration in 3D,”
Supercomputing Frontiers and Innovations, vol. 5, no. 4, December 2018.
DOI: 10.14529/jsfi180404
(720.15 KB)
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Batched BLAS (Basic Linear Algebra Subprograms) 2018 Specification
, July 2018.
(483.05 KB)

Batched One-Sided Factorizations of Tiny Matrices Using GPUs: Challenges and Countermeasures,”
Journal of Computational Science, vol. 26, pp. 226–236, May 2018.
DOI: 10.1016/j.jocs.2018.01.005
(3.73 MB)
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Big Data and Extreme-Scale Computing: Pathways to Convergence - Toward a Shaping Strategy for a Future Software and Data Ecosystem for Scientific Inquiry,”
The International Journal of High Performance Computing Applications, vol. 32, issue 4, pp. 435–479, July 2018.
DOI: 10.1177/1094342018778123
(1.29 MB)
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Computational Benefit of GPU Optimization for Atmospheric Chemistry Modeling,”
Journal of Advances in Modeling Earth Systems, vol. 10, issue 8, pp. 1952–1969, August 2018.
DOI: 10.1029/2018MS001276
(3.4 MB)
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Data Movement Interfaces to Support Dataflow Runtimes,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-18-03: University of Tennessee, May 2018.
(210.94 KB)
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The Design of Fast and Energy-Efficient Linear Solvers: On the Potential of Half-Precision Arithmetic and Iterative Refinement Techniques,”
International Conference on Computational Science (ICCS 2018), vol. 10860, Wuxi, China, Springer, pp. 586–600, June 2018.
DOI: 10.1007/978-3-319-93698-7_45
(487.88 KB)
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Distributed Termination Detection for HPC Task-Based Environments,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-18-14: University of Tennessee, June 2018.
“Do moldable applications perform better on failure-prone HPC platforms?,”
11th Workshop on Resiliency in High Performance Computing in Clusters, Clouds, and Grids, Turin, Italy, Springer Verlag, August 2018.
(360.72 KB)
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Evaluation and Design of FFT for Distributed Accelerated Systems,”
ECP WBS 2.3.3.09 Milestone Report, no. FFT-ECP ST-MS-10-1216: Innovative Computing Laboratory, University of Tennessee, October 2018.
(7.53 MB)
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Evaluation of Dataflow Programming Models for Electronic Structure Theory,”
Concurrency and Computation: Practice and Experience: Special Issue on Parallel and Distributed Algorithms, vol. 2018, issue e4490, pp. 1–20, May 2018.
DOI: 10.1002/cpe.4490
(1.69 MB)
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A Failure Detector for HPC Platforms,”
The International Journal of High Performance Computing Applications, vol. 32, issue 1, pp. 139–158, January 2018.
DOI: 10.1177/1094342017711505
(1.04 MB)
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