Timeline for Optimizing matrix-vector multiplication for many small matrices
Current License: CC BY-SA 3.0
9 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jun 7, 2018 at 10:23 | answer | added | Paul | timeline score: 5 | |
| Jan 11, 2014 at 14:43 | history | tweeted | twitter.com/#!/StackSciComp/status/422015831984582656 | ||
| Jan 11, 2014 at 14:33 | answer | added | Bill Barth | timeline score: 4 | |
| Jan 11, 2014 at 13:10 | answer | added | Wolfgang Bangerth | timeline score: 7 | |
| Jan 11, 2014 at 12:17 | comment | added | tpg2114 | @ChristianWaluga They are 5x5 up to maybe 10x10 sometimes, dense, not symmetric and not diagonally dominant generally speaking. How many times it needs to be done varies on the case, but typically 10000 to 60000 times per time step | |
| Jan 11, 2014 at 12:16 | comment | added | tpg2114 | @BrianBorchers There's no re-using the matrix, it's different for every point every time step | |
| Jan 11, 2014 at 6:36 | comment | added | Christian Waluga | I doubt that using the techniques for large matrices for a large block-diagonal will give you a significant speedup. How small is 'small' in your case and how many matrices are we typically talking about? Do you know anything else about these matrices, e.g., do they describe rotations etc.? | |
| Jan 11, 2014 at 5:20 | comment | added | Brian Borchers | Do you have to multiply the same matrix times many vectors or is there no reuse of the matrices? | |
| Jan 11, 2014 at 0:13 | history | asked | tpg2114 | CC BY-SA 3.0 |