Fast and Scalable Hierarchical Algorithms for Computational Linear Algebra
Principal Investigators :
- Dr. Olivier Coulaud, HIEPACS project-team, Inria Bordeaux Sud Ouest
- Prof. Eric Darve, Stanford University
- Dr. X.S. Li, Lawrence Berkeley National Lab
- Fast Multipole Method: The focus is on developing and on improving methods based on interpolation formulations (Chebyschev, equispaced points) and their efficiency and ease of use in the context of dislocation kernels.
- Sparse Linear Solvers: Study the use of low rank techniques (H-matrix like) to design fast direct and hybrid solvers able to compute data-sparse approximation of Schur complements.
- Improved parallelism for modern computers for heterogeneous manycores: Improvement of the parallel performance and scalability using hybrid parallelism and a task based programming model.
Publications and Awards:
- 9 Journal articles
- 12 Conference and Workshop papers.
E. Agullo, B. Bramas, O. Coulaud, E. Darve, M. Messner, T. Takahashi, Taskbased FMM for Multicore Architectures, SIAM Journal on Scientific Computing. vol 36, num 1, 2014.
Follow up :
The team was renewed for 3 years in 2015 to pursue its collaboration along the aforementioned topics involving many PhD and post-docs in addition to the senior researchers of each group.