Modeling 1D Distributed-Memory Dense Kernels for an Asynchronous Multifrontal Sparse Solver. - Patrick Amestoy; Jean-Yves L'Excellent; François-Henry Rouet; Wissam M. Sid-Lakhdar (VECPAR, 2014)

A study of shared-memory parallelism in a multifrontal solver. - Jean-Yves L'Excellent; Wissam M. Sid-Lakhdar (Parallel Comput., 2014)

A survey of direct methods for sparse linear systems. - Timothy A. Davis 001; Sivasankaran Rajamanickam; Wissam M. Sid-Lakhdar (Acta Numer., 2016)

Algorithm 980: Sparse QR Factorization on the GPU. - Sencer Nuri Yeralan; Timothy A. Davis 001; Wissam M. Sid-Lakhdar; Sanjay Ranka (ACM Trans. Math. Softw., 2017)

Multitask and Transfer Learning for Autotuning Exascale Applications. - Wissam M. Sid-Lakhdar; Mohsen Mahmoudi Aznaveh; Xiaoye S. Li; James Weldon Demmel (CoRR, 2019)

A parallel hierarchical blocked adaptive cross approximation algorithm. - Yang Liu 179; Wissam M. Sid-Lakhdar; Elizaveta Rebrova; Pieter Ghysels; Xiaoye Sherry Li (Int. J. High Perform. Comput. Appl., 2020)

GPTune: multitask learning for autotuning exascale applications. - Yang Liu 179; Wissam M. Sid-Lakhdar; Osni Marques; Xinran Zhu; Chang Meng; James Weldon Demmel; Xiaoye S. Li (PPoPP, 2021)

Deep Gaussian process with multitask and transfer learning for performance optimization. - Wissam M. Sid-Lakhdar; Mohsen Aznaveh; Piotr Luszczek; Jack J. Dongarra (HPEC, 2022)

PAQR: Pivoting Avoiding QR factorization. - Wissam M. Sid-Lakhdar; Sébastien Cayrols; Daniel Bielich; Ahmad Abdelfattah; Piotr Luszczek; Mark Gates; Stanimire Tomov; Hans Johansen; David B. Williams-Young; Timothy A. Davis 001; Jack J. Dongarra; Hartwig Anzt (IPDPS, 2023)

Combining multitask and transfer learning with deep Gaussian processes for autotuning-based performance engineering. - Piotr Luszczek; Wissam M. Sid-Lakhdar; Jack J. Dongarra (Int. J. High Perform. Comput. Appl., 2023)