New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Tridiagonal eigensolver, reduce gemm complexity taking advantage of the matrix shapes. #917

Open

5 tasks

rasolca opened this issue Jun 23, 2023 · 0 comments

Labels

Priority:High TODO:Epic Type:Optimization Type:Performance issue

Milestone

Collaborator

rasolca commented Jun 23, 2023 •

edited

The following steps are needed:

permute the eigenvectors to have the optimal shape (Permute (locally) to get the optimal matrix shape #914)
Implement the gemm with submatrices and make sure that gemm can be scheduled in a subtask (implement gemm for the tridiagonal solver #915)
Apply the new gemm to the tridiagonal eigensolver (Reduce gemm complexity in the tridiagonal eigensolver #916)

Work completed for

local implementation
distributed implementation

rasolca added Priority:High TODO:Epic Type:Performance issue Type:Optimization labels

rasolca added this to the Optimizations milestone

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment