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Funk, Y., M. Götz, and H. Anzt, Prediction of Optimal Solvers for Sparse Linear Systems Using Deep Learning,” 2022 SIAM Conference on Parallel Processing for Scientific Computing (PP), Philadelphia, PA, Society for Industrial and Applied Mathematics, pp. 14 - 24.
Tsai, Y-H. M., T. Cojean, and H. Anzt, Providing performance portable numerics for Intel GPUs,” Concurrency and Computation: Practice and Experience, vol. 17, October 2022.  (3.16 MB)
Schuchart, J., P. Nookala, T. Herault, E. F. Valeev, and G. Bosilca, Pushing the Boundaries of Small Tasks: Scalable Low-Overhead Data-Flow Programming in TTG,” 2022 IEEE International Conference on Cluster Computing (CLUSTER), Heidelberg, Germany, IEEE, September 2022.
Nance, D., S. Tomov, and K. Wong, A Python Library for Matrix Algebra on GPU and Multicore Architectures,” 2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS), Denver, CO, IEEE, December 2022.  (414.36 KB)
Sid-Lakhdar, W., S. Cayrols, D. Bielich, A. Abdelfattah, P. Luszczek, M. Gates, S. Tomov, H. Johansen, D. Williams-Young, T. Davis, et al., PAQR: Pivoting Avoiding QR factorization,” 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS), St. Petersburg, FL, USA, IEEE, 2023.
Ribizel, T., and H. Anzt, Parallel Symbolic Cholesky Factorization,” SC-W 2023: Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, Denver, CO, ACM, November 2023.
Mishler, D., J. Ciesko, S. Olivier, and G. Bosilca, Performance Insights into Device-initiated RMA Using Kokkos Remote Spaces,” 2023 IEEE International Conference on Cluster Computing Workshops (CLUSTER Workshops), Santa Fe, NM, USA, IEEE, November 2023.
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.