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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)
Cao, Q., T. Herault, A. Bouteiller, J. Schuchart, and G. Bosilca, Evaluating PaRSEC Through Matrix Computations in Scientific Applications,” Asynchronous Many-Task Systems and Applications - Second International Workshop, WAMTA 2024, Knoxville, TN, USA, February 14-16, 2024, Proceedings, vol. 14626: Springer, pp. 22–33, 2024. DOI: 10.1007/978-3-031-61763-8_3 (600.76 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)
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)
Cao, Q., Y. Pei, T. Herault, K. Akbudak, A. Mikhalev, G. Bosilca, H. Ltaief, D. Keyes, and J. Dongarra, Performance Analysis of Tile Low-Rank Cholesky Factorization Using PaRSEC Instrumentation Tools,” Workshop on Programming and Performance Visualization Tools (ProTools 19) at SC19, Denver, CO, ACM, November 2019.  (429.55 KB)
Cao, Q., G. Bosilca, N. Losada, W. Wu, D. Zhong, and J. Dongarra, Evaluating Data Redistribution in PaRSEC,” IEEE Transactions on Parallel and Distributed Systems, vol. 33, no. 8, pp. 1856-1872, August 2022. DOI: 10.1109/TPDS.2021.3131657 (3.19 MB)
Cao, Q., Y. Pei, K. Akbudak, G. Bosilca, H. Ltaief, D. Keyes, and J. Dongarra, Leveraging PaRSEC Runtime Support to Tackle Challenging 3D Data-Sparse Matrix Problems,” 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2021), Portland, OR, IEEE, May 2021.  (1.08 MB)