Publications

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Conference Paper
Danalis, A., H. Jagode, H. Hanumantharayappa, S. Ragate, and J. Dongarra, Counter Inspection Toolkit: Making Sense out of Hardware Performance Events,” 11th International Workshop on Parallel Tools for High Performance Computing, Dresden, Germany, Cham, Switzerland: Springer, February 2019. DOI: 10.1007/978-3-030-11987-4_2  (216.39 KB)
Yamazaki, I., S. Tomov, and J. Dongarra, Deflation Strategies to Improve the Convergence of Communication-Avoiding GMRES,” 5th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, New Orleans, LA, November 2014.  (465.52 KB)
Yamazaki, I., J. Kurzak, P. Luszczek, and J. Dongarra, Design and Implementation of a Large Scale Tree-Based QR Decomposition Using a 3D Virtual Systolic Array and a Lightweight Runtime,” Workshop on Large-Scale Parallel Processing, IPDPS 2014, Phoenix, AZ, IEEE, May 2014.  (398.16 KB)
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. DOI: DOI:10.1016/j.procs.2017.05.138  (446.14 KB)
Kabir, K., A. Haidar, S. Tomov, and J. Dongarra, On the Design, Development, and Analysis of Optimized Matrix-Vector Multiplication Routines for Coprocessors,” ISC High Performance 2015, Frankfurt, Germany, July 2015.  (1.49 MB)
Cao, C., G. Bosilca, T. Herault, and J. Dongarra, Design for a Soft Error Resilient Dynamic Task-based Runtime,” 29th IEEE International Parallel & Distributed Processing Symposium (IPDPS), Hyderabad, India, IEEE, May 2015.  (2.31 MB)
Brown, C., A. Abdelfattah, S. Tomov, and J. Dongarra, Design, Optimization, and Benchmarking of Dense Linear Algebra Algorithms on AMD GPUs,” 2020 IEEE High Performance Extreme Computing Virtual Conference: IEEE, September 2020.  (476.36 KB)
Faverge, M., J. Herrmann, J. Langou, B. Lowery, Y. Robert, and J. Dongarra, Designing LU-QR Hybrid Solvers for Performance and Stability,” IPDPS 2014, Phoenix, AZ, IEEE, May 2014. DOI: 10.1109/IPDPS.2014.108  (4.2 MB)
Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, On the Development of Variable Size Batched Computation for Heterogeneous Parallel Architectures,” The 17th IEEE International Workshop on Parallel and Distributed Scientific and Engineering Computing (PDSEC 2016), IPDPS 2016, Chicago, IL, IEEE, May 2016.  (708.62 KB)
Herault, T., Y. Robert, G. Bosilca, R. Harrison, C. Lewis, E. Valeev, and J. Dongarra, Distributed-Memory Multi-GPU Block-Sparse Tensor Contraction for Electronic Structure,” 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2021), Portland, OR, IEEE, May 2021.
Le Fèvre, V., G. Bosilca, A. Bouteiller, T. Herault, A. Hori, Y. Robert, and J. Dongarra, 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)
Donfack, S., S. Tomov, and J. Dongarra, Dynamically balanced synchronization-avoiding LU factorization with multicore and GPUs,” Fourth International Workshop on Accelerators and Hybrid Exascale Systems (AsHES), IPDPS 2014, May 2014.  (490.08 KB)
Anzt, H., J. Dongarra, M. Kreutzer, G. Wellein, and M. Kohler, Efficiency of General Krylov Methods on GPUs – An Experimental Study,” The Sixth International Workshop on Accelerators and Hybrid Exascale Systems (AsHES), Chicago, IL, IEEE, May 2016. DOI: 10.1109/IPDPSW.2016.45  (285.28 KB)
Haidar, A., P. Luszczek, S. Tomov, and J. Dongarra, Efficient Eigensolver Algorithms on Accelerator Based Architectures,” 2015 SIAM Conference on Applied Linear Algebra (SIAM LA), Atlanta, GA, SIAM, October 2015.  (6.98 MB)
Solcà, R., A. Kozhevnikov, A. Haidar, S. Tomov, T. C. Schulthess, and J. Dongarra, Efficient Implementation Of Quantum Materials Simulations On Distributed CPU-GPU Systems,” The International Conference for High Performance Computing, Networking, Storage and Analysis (SC15), Austin, TX, ACM, November 2015.  (1.09 MB)
Turchenko, V., G. Bosilca, A. Bouteiller, and J. Dongarra, Efficient Parallelization of Batch Pattern Training Algorithm on Many-core and Cluster Architectures,” 7th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, Berlin, Germany, September 2013.  (102.51 KB)
London, K., J. Dongarra, S. Moore, P. Mucci, K. Seymour, and T. Spencer, End-user Tools for Application Performance Analysis, Using Hardware Counters,” International Conference on Parallel and Distributed Computing Systems, Dallas, TX, August 2001.  (306.54 KB)
Anzt, H., S. Tomov, and J. Dongarra, Energy Efficiency and Performance Frontiers for Sparse Computations on GPU Supercomputers,” Sixth International Workshop on Programming Models and Applications for Multicores and Manycores (PMAM '15), San Francisco, CA, ACM, February 2015. DOI: 10.1145/2712386.2712387  (2.29 MB)
Anzt, H., Y. M. Tsai, A. Abdelfattah, T. Cojean, and J. Dongarra, Evaluating the Performance of NVIDIA’s A100 Ampere GPU for Sparse and Batched Computations,” 2020 IEEE/ACM Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS): IEEE, November 2020.  (1.9 MB)
Pei, Y., G. Bosilca, I. Yamazaki, A. Ida, and J. Dongarra, Evaluation of Programming Models to Address Load Imbalance on Distributed Multi-Core CPUs: A Case Study with Block Low-Rank Factorization,” PAW-ATM Workshop at SC19, Denver, CO, ACM, November 2019.  (4.51 MB)
Dongarra, J., K. London, S. Moore, P. Mucci, D. Terpstra, H. You, and M. Zhou, Experiences and Lessons Learned with a Portable Interface to Hardware Performance Counters,” PADTAD Workshop, IPDPS 2003, Nice, France, IEEE, April 2003.  (432.57 KB)
Cao, Q., Y. Pei, K. Akbudak, A. Mikhalev, G. Bosilca, H. Ltaief, D. Keyes, and J. Dongarra, Extreme-Scale Task-Based Cholesky Factorization Toward Climate and Weather Prediction Applications,” Platform for Advanced Scientific Computing Conference (PASC20), Geneva, Switzerland, ACM, June 2020. DOI: 10.1145/3394277.3401846  (2.71 MB)
Dong, T., A. Haidar, S. Tomov, and J. Dongarra, A Fast Batched Cholesky Factorization on a GPU,” International Conference on Parallel Processing (ICPP-2014), Minneapolis, MN, September 2014.  (1.37 MB)
Abdelfattah, A., S. Tomov, and J. Dongarra, Fast Batched Matrix Multiplication for Small Sizes using Half Precision Arithmetic on GPUs,” 33rd IEEE International Parallel and Distributed Processing Symposium (IPDPS), Rio de Janeiro, Brazil, IEEE, May 2019.  (675.5 KB)
Anzt, H., G. Collins, J. Dongarra, G. Flegar, and E. S. Quintana-Orti, Flexible Batched Sparse Matrix-Vector Product on GPUs,” 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA '17), Denver, CO, ACM Press, November 2017. DOI: http://dx.doi.org/10.1145/3148226.3148230  (583.4 KB)
Cao, Q., G. Bosilca, W. Wu, D. Zhong, A. Bouteiller, and J. Dongarra, Flexible Data Redistribution in a Task-Based Runtime System,” IEEE International Conference on Cluster Computing (Cluster 2020), Kobe, Japan, IEEE, September 2020. DOI: 10.1109/CLUSTER49012.2020.00032  (354.8 KB)
Haidar, A., A. YarKhan, C. Cao, P. Luszczek, S. Tomov, and J. Dongarra, Flexible Linear Algebra Development and Scheduling with Cholesky Factorization,” 17th IEEE International Conference on High Performance Computing and Communications, Newark, NJ, August 2015.  (494.31 KB)
Haidar, A., T. Dong, S. Tomov, P. Luszczek, and J. Dongarra, Framework for Batched and GPU-resident Factorization Algorithms to Block Householder Transformations,” ISC High Performance, Frankfurt, Germany, Springer, July 2015.  (778.26 KB)
Cao, Q., R. Alomairy, Y. Pei, G. Bosilca, H. Ltaief, D. Keyes, and J. Dongarra, A Framework to Exploit Data Sparsity in Tile Low-Rank Cholesky Factorization,” IEEE International Parallel and Distributed Processing Symposium (IPDPS), July 2022. DOI: 10.1109/IPDPS53621.2022.00047  (1.03 MB)
Bosilca, G., A. Bouteiller, A. Danalis, T. Herault, and J. Dongarra, From Serial Loops to Parallel Execution on Distributed Systems,” International European Conference on Parallel and Distributed Computing (Euro-Par '12), Rhodes, Greece, August 2012.  (203.08 KB)
Herault, T., Y. Robert, G. Bosilca, and J. Dongarra, Generic Matrix Multiplication for Multi-GPU Accelerated Distributed-Memory Platforms over PaRSEC,” ScalA'19: 10th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Denver, CO, IEEE, November 2019.  (260.69 KB)
Anzt, H., E. Ponce, G. D. Peterson, and J. Dongarra, GPU-accelerated Co-design of Induced Dimension Reduction: Algorithmic Fusion and Kernel Overlap,” 2nd International Workshop on Hardware-Software Co-Design for High Performance Computing, Austin, TX, ACM, November 2015.  (1.46 MB)
Wu, W., G. Bosilca, R. vandeVaart, S. Jeaugey, and J. Dongarra, GPU-Aware Non-contiguous Data Movement In Open MPI,” 25th International Symposium on High-Performance Parallel and Distributed Computing (HPDC'16), Kyoto, Japan, ACM, June 2016. DOI: http://dx.doi.org/10.1145/2907294.2907317  (482.32 KB)
Luo, X., W. Wu, G. Bosilca, Y. Pei, Q. Cao, T. Patinyasakdikul, D. Zhong, and J. Dongarra, HAN: A Hierarchical AutotuNed Collective Communication Framework,” IEEE Cluster Conference, Kobe, Japan, Best Paper Award, IEEE Computer Society Press, September 2020.  (764.05 KB)
Wong, K., S. Tomov, and J. Dongarra, Hands-on Research and Training in High-Performance Data Sciences, Data Analytics, and Machine Learning for Emerging Environments,” ISC High Performance, Frankfurt, Germany, Springer International Publishing, June 2019.  (1016.52 KB)
Haidar, A., S. Tomov, J. Dongarra, and N. J. Higham, Harnessing GPU Tensor Cores for Fast FP16 Arithmetic to Speed up Mixed-Precision Iterative Refinement Solvers,” The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), Dallas, TX, IEEE, November 2018. DOI: 10.1109/SC.2018.00050  (642.51 KB)
Ayala, A., S. Tomov, A. Haidar, and J. Dongarra, heFFTe: Highly Efficient FFT for Exascale,” International Conference on Computational Science (ICCS 2020), Amsterdam, Netherlands, June 2020. DOI: 10.1007/978-3-030-50371-0_19  (2.62 MB)
Jia, Y., P. Luszczek, and J. Dongarra, Hessenberg Reduction with Transient Error Resilience on GPU-Based Hybrid Architectures,” 30th IEEE International Parallel & Distributed Processing Symposium (IPDPS), Chicago, IL, IEEE, May 2016.  (535.72 KB)
Haidar, A., P. Luszczek, S. Tomov, and J. Dongarra, Heterogeneous Acceleration for Linear Algebra in Mulit-Coprocessor Environments,” VECPAR 2014, Eugene, OR, June 2014.  (276.52 KB)
Newburn, C. J., G. Bansal, M. Wood, L. Crivelli, J. Planas, A. Duran, P. Souza, L. Borges, P. Luszczek, S. Tomov, et al., Heterogeneous Streaming,” The Sixth International Workshop on Accelerators and Hybrid Exascale Systems (AsHES), IPDPS 2016, Chicago, IL, IEEE, May 2016.  (2.73 MB)
Wu, W., A. Bouteiller, G. Bosilca, M. Faverge, and J. Dongarra, Hierarchical DAG scheduling for Hybrid Distributed Systems,” 29th IEEE International Parallel & Distributed Processing Symposium (IPDPS), Hyderabad, India, IEEE, May 2015.  (1.11 MB)
Beams, N., A. Abdelfattah, S. Tomov, J. Dongarra, T. Kolev, and Y. Dudouit, High-Order Finite Element Method using Standard and Device-Level Batch GEMM on GPUs,” 2020 IEEE/ACM 11th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA): IEEE, November 2020.  (1.3 MB)
Haidar, A., A. Abdelfattah, S. Tomov, and J. Dongarra, High-performance Cholesky Factorization for GPU-only Execution,” Proceedings of the General Purpose GPUs (GPGPU-10), Austin, TX, ACM, February 2017. DOI: 10.1145/3038228.3038237  (872.18 KB)
Masliah, I., A. Abdelfattah, A. Haidar, S. Tomov, J. Falcou, and J. Dongarra, High-performance Matrix-matrix Multiplications of Very Small Matrices,” 22nd International European Conference on Parallel and Distributed Computing (Euro-Par'16), Grenoble, France, Springer International Publishing, August 2016.
Abdelfattah, A., M. Baboulin, V. Dobrev, J. Dongarra, C. Earl, J. Falcou, A. Haidar, I. Karlin, T. Kolev, I. Masliah, et al., High-Performance Tensor Contractions for GPUs,” International Conference on Computational Science (ICCS'16), San Diego, CA, June 2016.  (2.36 MB)
Lukarski, D., H. Anzt, S. Tomov, and J. Dongarra, Hybrid Multi-Elimination ILU Preconditioners on GPUs,” International Heterogeneity in Computing Workshop (HCW), IPDPS 2014, Phoenix, AZ, IEEE, May 2014.  (1.67 MB)
Ayala, A., S. Tomov, X. Luo, H. Shaiek, A. Haidar, G. Bosilca, and J. Dongarra, Impacts of Multi-GPU MPI Collective Communications on Large FFT Computation,” Workshop on Exascale MPI (ExaMPI) at SC19, Denver, CO, November 2019.  (1.6 MB)
Haidar, A., P. Luszczek, J. Kurzak, and J. Dongarra, An Improved Parallel Singular Value Algorithm and Its Implementation for Multicore Hardware,” Supercomputing 2013, Denver, CO, November 2013.
Yamazaki, I., H. Anzt, S. Tomov, M. Hoemmen, and J. Dongarra, Improving the performance of CA-GMRES on multicores with multiple GPUs,” IPDPS 2014, Phoenix, AZ, IEEE, May 2014.  (333.82 KB)
Lindquist, N., P. Luszczek, and J. Dongarra, Improving the Performance of the GMRES Method using Mixed-Precision Techniques,” Smoky Mountains Computational Sciences & Engineering Conference (SMC2020), August 2020.  (600.33 KB)

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