Publications

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Conference Paper
Gates, M., S. Tomov, and A. Haidar, Comparing Hybrid CPU-GPU and Native GPU-only Acceleration for Linear Algebra,” 2015 SIAM Conference on Applied Linear Algebra, Atlanta, GA, SIAM, October 2015.  (4.7 MB)
Moore, S., A Comparison of Counting and Sampling Modes of Using Performance Monitoring Hardware,” International Conference on Computational Science (ICCS 2002), Amsterdam, Netherlands, Springer, April 2002. DOI: 10.1007/3-540-46080-2_95  (122 KB)
Baboulin, M., J. Dongarra, and R. Lacroix, Computing Least Squares Condition Numbers on Hybrid Multicore/GPU Systems,” International Interdisciplinary Conference on Applied Mathematics, Modeling and Computational Science (AMMCS), Waterloo, Ontario, CA, August 2014.  (130.18 KB)
Aupy, G., A. Benoit, L. Pottier, P. Raghavan, Y. Robert, and M. Shantharam, Co-Scheduling Algorithms for Cache-Partitioned Systems,” 19th Workshop on Advances in Parallel and Distributed Computational Models, Orlando, FL, IEEE Computer Society Press, May 2017. DOI: 10.1109/IPDPSW.2017.60  (584.76 KB)
Aupy, G., A. Benoit, B. Goglin, L. Pottier, and Y. Robert, Co-Scheduling HPC Workloads on Cache-Partitioned CMP Platforms,” Cluster 2018, Belfast, UK, IEEE Computer Society Press, September 2018.  (423.75 KB)
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)
Haidar, A., J. Kurzak, G. Pichon, and M. Faverge, A Data Flow Divide and Conquer Algorithm for Multicore Architecture,” 29th IEEE International Parallel & Distributed Processing Symposium (IPDPS), Hyderabad, India, IEEE, May 2015.  (535.44 KB)
Beck, M., T. Moore, N. French, E. Kissel, and M. Swany, Data Logistics: Toolkit and Applications,” 5th EAI International Conference on Smart Objects and Technologies for Social Good, Valencia, Spain, September 2019.  (6.71 MB)
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)
Benoit, A., V. Le Fèvre, P. Raghavan, Y. Robert, and H. Sun, Design and Comparison of Resilient Scheduling Heuristics for Parallel Jobs,” 22nd Workshop on Advances in Parallel and Distributed Computational Models (APDCM 2020), New Orleans, LA, IEEE Computer Society Press, May 2020.  (696.21 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)
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)
Marin, G., C. McCurdy, and J. Vetter, Diagnosis and Optimization of Application Prefetching Performance,” Proceedings of the 27th ACM International Conference on Supercomputing (ICS '13), Eugene, Oregon, USA, ACM Press, June 2013. DOI: 10.1145/2464996.2465014  (827.31 KB)
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)
Zaitsev, D., and P. Luszczek, Docker Container based PaaS Cloud Computing Comprehensive Benchmarks using LAPACK,” Computer Modeling and Intelligent Systems CMIS-2020, Zaporizhzhoa, March 2020.  (451.33 KB)
Yamazaki, I., S. Rajamanickam, E. G. Boman, M. Hoemmen, M. A. Heroux, and S. Tomov, Domain Decomposition Preconditioners for Communication-Avoiding Krylov Methods on a Hybrid CPU/GPU Cluster,” The International Conference for High Performance Computing, Networking, Storage and Analysis (SC 14), New Orleans, LA, IEEE, November 2014.
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)
Zhao, Y., L. Wan, W. Wu, G. Bosilca, R. Vuduc, J. Ye, W. Tang, and Z. Xu, Efficient Communications in Training Large Scale Neural Networks,” ACM MultiMedia Workshop 2017, Mountain View, CA, ACM, October 2017.  (1.41 MB)
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)
Han, L., Y. Gao, J. Liu, Y. Robert, and F. Vivien, Energy-Aware Strategies for Reliability-Oriented Real-Time Task Allocation on Heterogeneous Platforms,” 49th International Conference on Parallel Processing (ICPP 2020), Edmonton, AB, Canada, ACM Press, 2020.  (804.96 KB)
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)
Extreme-Scale Task-Based Cholesky Factorization Toward Climate and Weather Prediction Applications,” The Platform for Advanced Scientific Computing Conference (PASC20), Geneva, Switzerland, ACM, July 2021.
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)
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)
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)
Han, L., V. Le Fèvre, L-C. Canon, Y. Robert, and F. Vivien, A Generic Approach to Scheduling and Checkpointing Workflows,” The 47th International Conference on Parallel Processing (ICPP 2018), Eugene, OR, IEEE Computer Society Press, August 2018.  (737.11 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)
Patinyasakdikul, T., D. Eberius, G. Bosilca, and N. Hjelm, Give MPI Threading a Fair Chance: A Study of Multithreaded MPI Designs,” IEEE Cluster, Albuquerque, NM, IEEE, September 2019.  (220.84 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)
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)

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