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M. Lopez, G., W. Joubert, V. Larrea, O. Hernandez, A. Haidar, S. Tomov, and J. Dongarra, “Evaluation of Directive-Based Performance Portable Programming Models,” International Journal of High Performance Computing and Networking, To appear.

Dongarra, J., M. Gates, A. Haidar, J. Kurzak, P. Luszczek, P. Wu, I. Yamazaki, A. YarKhan, M. Abalenkovs, N. Bagherpour, et al., “PLASMA: Parallel Linear Algebra Software for Multicore Using OpenMP,” ACM Transactions on Mathematical Software, To appear.

(7.5 MB)

2019

Masliah, I., A. Abdelfattah, A. Haidar, S. Tomov, M. Baboulin, J. Falcou, and J. Dongarra, “Algorithms and Optimization Techniques for High-Performance Matrix-Matrix Multiplications of Very Small Matrices,” Parallel Computing, vol. 81, pp. 1–21, January 2019.

Kaya, O., and Y. Robert, “Computing dense tensor decompositions with optimal dimension trees,” Algorithmica, to appear, 2019.

Beck, M., T. Moore, P. Luszczek, and A. Danalis, “Interoperable Convergence of Storage, Networking, and Computation,” FICC 2019, San Francisco, CA, Springer, March 14-15, 2019.

(2.64 MB)

Beck, M., T. Moore, and P. Luszczek, “Interoperable Convergence of Storage, Networking, and Computation,” Future of Information and Communication Conference (FICC), San Francisco, Science and Information (SAI), March 2019.

(1.8 MB)

Losada, N., G. Bosilca, A. Bouteiller, P. González, and M. J. Martín, “Local Rollback for Resilient MPI Applications with Application-Level Checkpointing and Message Logging,” Future Generation Computer Systems, vol. 91, pp. 450-464, February 2019.

(1.16 MB)

Charara, A., M. Gates, J. Kurzak, and J. Dongarra, “SLATE Developers' Guide,” SLATE Working Notes, no. 11, ICL-UT-19-02: Innovative Computing Laboratory, University of Tennessee, January 2019.

Gates, M., A. Charara, J. Kurzak, and J. Dongarra, “SLATE Users' Guide,” SLATE Working Notes, no. 10, ICL-UT-19-01: Innovative Computing Laboratory, University of Tennessee, January 2019.

2018

Dongarra, J., V. Getov, and K. Walsh, “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.

Jagode, H., A. Danalis, and J. Dongarra, “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.

(1.68 MB)

Dong, T., A. Haidar, S. Tomov, and J. Dongarra, “Accelerating the SVD Bi-Diagonalization of a Batch of Small Matrices using GPUs,” Journal of Computational Science, vol. 26, pp. 237–245, May 2018.

Gates, M., S. Tomov, and J. Dongarra, “Accelerating the SVD Two Stage Bidiagonal Reduction and Divide and Conquer Using GPUs,” Parallel Computing, vol. 74, pp. 3–18, May 2018.

Luo, X., W. Wu, G. Bosilca, T. Patinyasakdikul, L. Wang, and J. Dongarra, “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.

(493.65 KB)

Anzt, H., J. Dongarra, G. Flegar, N. J. Higham, and E. S. Quintana-Ortí, “Adaptive Precision in Block‐Jacobi Preconditioning for Iterative Sparse Linear System Solvers,” Concurrency Computation: Practice and Experience, March 2018.

Masliah, I., A. Abdelfattah, A. Haidar, S. Tomov, M. Baboulin, J. Falcou, and J. Dongarra, “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)

Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, “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.

Yamazaki, I., A. Abdelfattah, A. Ida, S. Ohshima, S. Tomov, R. Yokota, and J. Dongarra, “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)

Balaprakash, P., J. Dongarra, T. Gamblin, M. Hall, J. Hollingsworth, B. Norris, and R. Vuduc, “Autotuning in High-Performance Computing Applications,” Proceedings of the IEEE, vol. 106, issue 11, pp. 2068–2083, November 2018.

Dongarra, J., M. Gates, J. Kurzak, P. Luszczek, and Y. Tsai, “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.

Luszczek, P., J. Kurzak, I. Yamazaki, D. Keffer, V. Maroulas, and J. Dongarra, “Autotuning Techniques for Performance-Portable Point Set Registration in 3D,” Supercomputing Frontiers and Innovations, vol. 5, no. 4, December 2018.

(720.15 KB)

Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, “Batched One-Sided Factorizations of Tiny Matrices Using GPUs: Challenges and Countermeasures,” Journal of Computational Science, vol. 26, pp. 226–236, May 2018.

(3.73 MB)

Marques, O., J. Demmel, and P. B. Vasconcelos, “Bidiagonal SVD Computation via an Associated Tridiagonal Eigenproblem,” LAPACK Working Note, no. LAWN 295, ICL-UT-18-02: University of Tennessee, April 2018.

(1.53 MB)

Asch, M., T. Moore, R. M. Badia, M. Beck, P. Beckman, T. Bidot, F. Bodin, F. Cappello, A. Choudhary, B. R. de Supinski, et al., “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.

(1.29 MB)

Caniou, Y., E. Caron, A. Kong Win Chang, and Y. Robert, “Budget-Aware Scheduling Algorithms for Scientific Workflows with Stochastic Task Weights on Heterogeneous IaaS Cloud Platforms,” 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Vancouver, BC, Canada, IEEE, May 2018.

(1.31 MB)

Han, L., L-C. Canon, H. Casanova, Y. Robert, and F. Vivien, “Checkpointing Workflows for Fail-Stop Errors,” IEEE Transactions on Computers, vol. 67, issue 8, pp. 1105–1120, August 2018.

Sun, J., J. Fu, J. Drake, Q. Zhu, A. Haidar, M. Gates, S. Tomov, and J. Dongarra, “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.

Casanova, H., J. Herrmann, and Y. Robert, “Computing the Expected Makespan of Task Graphs in the Presence of Silent Errors,” Parallel Computing, vol. 75, pp. 41–60, July 2018.

(2.56 MB)

Benoit, A., A. Cavelan, F. Cappello, P. Raghavan, Y. Robert, and H. Sun, “Coping with Silent and Fail-Stop Errors at Scale by Combining Replication and Checkpointing,” Journal of Parallel and Distributed Computing, vol. 122, pp. 209–225, December 2018.

(837 KB)

Aupy, G., A. Benoit, S. Dai, L. Pottier, P. Raghavan, Y. Robert, and M. Shantharam, “Co-Scheduling Amdhal Applications on Cache-Partitioned Systems,” International Journal of High Performance Computing Applications, vol. 32, issue 1, pp. 123–138, January 2018.

(672.52 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)

Bouteiller, A., G. Bosilca, T. Herault, and J. Dongarra, “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)

Haidar, A., A. Abdelfattah, M. Zounon, P. Wu, S. Pranesh, S. Tomov, and J. Dongarra, “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.

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)

Tomov, S., A. Haidar, D. Schultz, and J. Dongarra, “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)

Jagode, H., A. Danalis, R. Hoque, M. Faverge, and J. Dongarra, “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.

(1.69 MB)

Bosilca, G., A. Bouteiller, A. Guermouche, T. Herault, Y. Robert, P. Sens, and J. Dongarra, “A Failure Detector for HPC Platforms,” The International Journal of High Performance Computing Applications, vol. 32, issue 1, pp. 139–158, January 2018.

(1.04 MB)

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)

Haidar, A., A. Abdelfattah, M. Zounon, S. Tomov, and J. Dongarra, “A Guide for Achieving High Performance with Very Small Matrices on GPUs: A Case Study of Batched LU and Cholesky Factorizations,” IEEE Transactions on Parallel and Distributed Systems, vol. 29, issue 5, pp. 973–984, May 2018.

(832.92 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.

Anzt, H., T. Gruetzmacher, E. Quintana-Orti, and F. Scheidegger, “High-Performance GPU Implementation of PageRank with Reduced Precision based on Mantissa Segmentation,” 8th Workshop on Irregular Applications: Architectures and Algorithms, 2018.

Abdelfattah, A., M. Gates, J. Kurzak, P. Luszczek, and J. Dongarra, “Implementation of the C++ API for Batch BLAS,” SLATE Working Notes, no. 7, ICL-UT-18-04: Innovative Computing Laboratory, University of Tennessee, June 2018.

(1.07 MB)

Anzt, H., T. Huckle, J. Bräckle, and J. Dongarra, “Incomplete Sparse Approximate Inverses for Parallel Preconditioning,” Parallel Computing, vol. 71, pp. 1–22, January 2018.

Ghysels, P., S. Li, A. YarKhan, and J. Dongarra, “Initial Integration and Evaluation of SLATE and STRUMPACK,” Innovative Computing Laboratory Technical Report, no. ICL-UT-18-11: University of Tennessee, December 2018.

(246.23 KB)

YarKhan, A., G. Ragghianti, J. Dongarra, M. Cawkwell, D. Perez, and A. Voter, “Initial Integration and Evaluation of SLATE Parallel BLAS in LATTE,” Innovative Computing Laboratory Technical Report, no. ICL-UT-18-07: Innovative Computing Laboratory, University of Tennessee, June 2018.

(366.6 KB)

Haidar, A., H. Jagode, P. Vaccaro, A. YarKhan, S. Tomov, and J. Dongarra, “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)

Anzt, H., and J. Dongarra, “A Jaccard Weights Kernel Leveraging Independent Thread Scheduling on GPUs,” SBAC-PAD, 2018.

(237.68 KB)

Gates, M., A. Charara, J. Kurzak, A. YarKhan, I. Yamazaki, and J. Dongarra, “Least Squares Performance Report,” SLATE Working Notes, no. 9, ICL-UT-18-10: Innovative Computing Laboratory, University of Tennessee, December 2018.

(1.76 MB)

Kurzak, J., M. Gates, I. Yamazaki, A. Charara, A. YarKhan, J. Finney, G. Ragghianti, P. Luszczek, and J. Dongarra, “Linear Systems Performance Report,” SLATE Working Notes, no. 8, ICL-UT-18-08: Innovative Computing Laboratory, University of Tennessee, September 2018.

(1.64 MB)

Benoit, A., A. Cavelan, Y. Robert, and H. Sun, “Multi-Level Checkpointing and Silent Error Detection for Linear Workflows,” Journal of Computational Science, vol. 28, pp. 398–415, September 2018.

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