Publications

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E
Eijkhout, V., On the Existence Problem of Incomplete Factorisation Methods,” University of Tennessee Computer Science Department Technical Report, no. UT-CS-99-435, December 1999.  (222.2 KB)
Eijkhout, V., Automatic Determination of Matrix-Blocks,” Lapack Working Note 151, University of Tennessee Computer Science Technical Report, no. UT-CS-01-458, January 2001.  (1.15 MB)
Eijkhout, V., and E. Fuentes, A Proposed Standard for Matrix Metadata,” Innovative Computing Laboratory Technical Report, no. ICL-UT-03-02, Submitted to ACM TOMS, November 2003.  (13.39 KB)
Eijkhout, V., Numerical Metadata API Reference,” Innovative Computing Laboratory Technical Report, February 2007.  (454.79 KB)
Kurzak, J., M. Gates, A. Charara, A. YarKhan, and J. Dongarra, 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.  (1.63 MB)
Eidson, T., J. Dongarra, and V. Eijkhout, Applying Aspect-Oriented Programming Concepts to a Component-based Programming Model,” IPDPS 2003, Workshop on NSF-Next Generation Software, Nice, France, March 2003.  (66.99 KB)
Eidson, T., V. Eijkhout, and J. Dongarra, Improvements in the Efficient Composition of Applications,” IPDPS 2004, NGS Workshop (to appear), Sante Fe, 00 2004.  (42.85 KB)
Eberius, D., T. Patinyasakdikul, and G. Bosilca, Using Software-Based Performance Counters to Expose Low-Level Open MPI Performance Information,” EuroMPI, Chicago, IL, ACM, September 2017.  (745.58 KB)
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Du, P., R. Weber, P. Luszczek, S. Tomov, G. D. Peterson, and J. Dongarra, From CUDA to OpenCL: Towards a Performance-portable Solution for Multi-platform GPU Programming,” Parallel Computing, vol. 38, no. 8, pp. 391-407, August 2012.  (1.64 MB)
Du, P., P. Luszczek, S. Tomov, and J. Dongarra, Soft Error Resilient QR Factorization for Hybrid System with GPGPU,” Journal of Computational Science, vol. 4, issue 6, pp. 457–464, November 2013.  (995.45 KB)
Du, P., P. Luszczek, and J. Dongarra, High Performance Dense Linear System Solver with Soft Error Resilience,” IEEE Cluster 2011, Austin, TX, September 2011.  (1.27 MB)
Du, Y., L. Marchal, G. Pallez, and Y. Robert, Robustness of the Young/Daly Formula for Stochastic Iterative Applications,” 49th International Conference on Parallel Processing (ICPP 2020), Edmonton, AB, Canada, ACM Press, August 2020.  (1.11 MB)
Du, P., A. Bouteiller, G. Bosilca, T. Herault, and J. Dongarra, Algorithm-Based Fault Tolerance for Dense Matrix Factorization,” Proceedings of the 17th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP 2012, New Orleans, LA, USA, ACM, pp. 225-234, February 2012.  (865.79 KB)
Du, P., A. Bouteiller, G. Bosilca, T. Herault, and J. Dongarra, Algorithm-based Fault Tolerance for Dense Matrix Factorizations,” University of Tennessee Computer Science Technical Report, no. UT-CS-11-676, Knoxville, TN, August 2011.  (865.79 KB)
Du, P., P. Luszczek, S. Tomov, and J. Dongarra, 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)
Du, P., P. Luszczek, and J. Dongarra, High Performance Dense Linear System Solver with Resilience to Multiple Soft Errors,” ICCS 2012, Omaha, NE, June 2012.  (1.27 MB)
Du, P., P. Luszczek, S. Tomov, and J. Dongarra, Soft Error Resilient QR Factorization for Hybrid System with GPGPU,” Journal of Computational Science, Seattle, WA, Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems at SC11, November 2011.  (965.88 KB)
Du, P., P. Luszczek, S. Tomov, and J. Dongarra, Soft Error Resilient QR Factorization for Hybrid System,” University of Tennessee Computer Science Technical Report, no. UT-CS-11-675, Knoxville, TN, July 2011.  (1.39 MB)
Du, P., P. Luszczek, S. Tomov, and J. Dongarra, Soft Error Resilient QR Factorization for Hybrid System,” UT-CS-11-675 (also LAPACK Working Note #252), no. ICL-CS-11-675, July 2011.  (1.39 MB)
Du, P., M. Parsons, E. Fuentes, S-L. Shaw, and J. Dongarra, Tuning Principal Component Analysis for GRASS GIS on Multi-core and GPU Architectures,” FOSS4G 2010, Barcelona, Spain, September 2010.  (1.57 MB)
Du, P., P. Luszczek, and J. Dongarra, OpenCL Evaluation for Numerical Linear Algebra Library Development,” Symposium on Application Accelerators in High-Performance Computing (SAAHPC '10), Knoxville, TN, July 2010.  (2.69 MB)
Du, Y., G. Pallez, L. Marchal, and Y. Robert, Optimal Checkpointing Strategies for Iterative Applications,” IEEE Transactions on Parallel Distributed Systems, vol. 33, issue 3, pp. 507-522, March 2022.  (1.47 MB)
Du, P., S. Tomov, and J. Dongarra, Providing GPU Capability to LU and QR within the ScaLAPACK Framework,” University of Tennessee Computer Science Technical Report (also LAWN 272), no. UT-CS-12-699, September 2012.  (7.48 MB)
Aggarwal, I., P. Nayak, A. Kashi, and H. Anzt, Preconditioners for Batched Iterative Linear Solvers on GPUs,” Smoky Mountains Computational Sciences and Engineering Conference, vol. 169075: Springer Nature Switzerland, pp. 38 - 53, January 2023.
Dorris, J., A. YarKhan, J. Kurzak, P. Luszczek, and J. Dongarra, Task Based Cholesky Decomposition on Xeon Phi Architectures using OpenMP,” International Journal of Computational Science and Engineering (IJCSE), vol. 17, no. 3, October 2018.
Doolin, D., J. Dongarra, and K. Seymour, JLAPACK - Compiling LAPACK Fortran to Java,” Scientific Programming, vol. 7, no. 2, pp. 111-138, October 2002.  (307.46 KB)
Dongarra, J., H. Meuer, and E. Strohmaier, Top500 Supercomputer Sites (13th edition),” University of Tennessee Computer Science Department Technical Report, no. UT-CS-99-425, June 1999.  (278.51 KB)
Dongarra, J., Z. Chen, G. Bosilca, and J. Langou, Disaster Survival Guide in Petascale Computing: An Algorithmic Approach,” in Petascale Computing: Algorithms and Applications (to appear): Chapman & Hall - CRC Press, 00 2007.  (260.18 KB)
Dongarra, J., P. Beckman, P. Aerts, F. Cappello, T. Lippert, S. Matsuoka, P. Messina, T. Moore, R. Stevens, A. Trefethen, et al., The International Exascale Software Project: A Call to Cooperative Action by the Global High Performance Community,” International Journal of High Performance Computing Applications (to appear), July 2009.  (203.04 KB)
Dongarra, J., and P. Luszczek, High Performance Development for High End Computing with Python Language Wrapper (PLW),” International Journal for High Performance Computer Applications, vol. 21, no. 3, pp. 360-369, 00 2007.  (179.32 KB)
Dongarra, J., Report on the TianHe-2A System,” Innovative Computing Laboratory Technical Report, no. ICL-UT-17-04: University of Tennessee, September 2017.  (7.15 MB)
Dongarra, J., High Performance Computing Trends, Supercomputers, Clusters, and Grids,” Information Processing Society of Japan Symposium Series, vol. 2003, no. 14, pp. 55-58, January 2003.
Dongarra, J., A Tribute to Gene Golub,” Computing in Science and Engineering: IEEE, pp. 5, January 2008.
Dongarra, J., and D. W. Walker, The Quest for Petascale Computing,” Computing in Science and Engineering, vol. 3, no. 3, pp. 32-39, May 2001.  (178.3 KB)
Dongarra, J., M. Gates, P. Luszczek, and S. Tomov, Translational Process: Mathematical Software Perspective,” Journal of Computational Science, September 2020.  (752.59 KB)
Dongarra, J., and V. Eijkhout, Self-Adapting Numerical Software and Automatic Tuning of Heuristics,” Lecture Notes in Computer Science, vol. 2660, Melbourne, Australia, Springer Verlag, pp. 759-770, June 2003.  (45.95 KB)
Dongarra, J., Performance of Various Computers Using Standard Linear Equations Software (Linpack Benchmark Report),” University of Tennessee Computer Science Technical Report, UT-CS-89-85, 00 2010.  (6.42 MB)
Dongarra, J., S. Hammarling, N. J. Higham, S. Relton, P. Valero-Lara, and M. Zounon, The Design and Performance of Batched BLAS on Modern High-Performance Computing Systems,” International Conference on Computational Science (ICCS 2017), Zürich, Switzerland, Elsevier, June 2017.  (446.14 KB)
Dongarra, J., and S. Moore, Empirical Performance Tuning of Dense Linear Algebra Software,” in Performance Tuning of Scientific Applications (to appear), 00 2010.
Dongarra, J., and V. Eijkhout, Finite-choice Algorithm Optimization in Conjugate Gradients (LAPACK Working Note 159),” University of Tennessee Computer Science Technical Report, UT-CS-03-502, January 2003.  (64.52 KB)
Dongarra, J., Performance of Various Computers Using Standard Linear Equations Software,” University of Tennessee Computer Science Technical Report, no. cs-89-85, February 2013.  (539.24 KB)
Dongarra, J., J. Demmel, P. Husbands, and P. Luszczek, HPCS Library Study Effort,” University of Tennessee Computer Science Technical Report, UT-CS-08-617, January 2008.  (73.22 KB)
Dongarra, J., M. Faverge, T. Herault, J. Langou, and Y. Robert, Hierarchical QR Factorization Algorithms for Multi-Core Cluster Systems,” IPDPS 2012, the 26th IEEE International Parallel and Distributed Processing Symposium, Shanghai, China, IEEE Computer Society Press, May 2012.  (405.71 KB)
Dongarra, J., H. Jagode, A. Danalis, D. Barry, and V. Weaver, Performance Application Programming Interface for Extreme-Scale Environments (PAPI-EX) (Poster) , Seattle, WA, 2020 NSF Cyberinfrastructure for Sustained Scientific Innovation (CSSI) Principal Investigator Meeting, 20 2020.  (2.53 MB)
Dongarra, J., and A. Geist, Report on the Oak Ridge National Laboratory's Frontier System,” ICL Technical Report, no. ICL-UT-22-05, May 2022.  (16.87 MB)
Dongarra, J., H. Meuer, and E. Strohmaier, Top500 Supercomputer Sites (15th edition),” University of Tennessee Computer Science Department Technical Report, no. UT-CS-00-442, June 2000.  (278.88 KB)
Dongarra, J., Performance of Various Computers Using Standard Linear Equations Software (Linpack Benchmark Report),” University of Tennessee Computer Science Technical Report, no. CS-89-85, 00 2011.  (6.42 MB)
Dongarra, J., S. Gottlieb, and W. T. Kramer, Race to Exascale,” Computing in Science and Engineering, vol. 21, issue 1, pp. 4-5, March 2019.  (106.97 KB)
Dongarra, J., M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, and I. Yamazaki, Accelerating Numerical Dense Linear Algebra Calculations with GPUs,” Numerical Computations with GPUs: Springer International Publishing, pp. 3-28, 2014.  (1.06 MB)
Dongarra, J., Performance of Various Computers Using Standard Linear Equations Software (Linpack Benchmark Report),” University of Tennessee Computer Science Department Technical Report, CS-89-85, January 2004.  (6.42 MB)

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