Ticket #4024 (closed Patches: fixed)
improve performance of inplace_solve
|Reported by:||guwi17||Owned by:||guwi17|
|Keywords:||performance, triangular solve, inplace solve||Cc:||consulting@…|
Joern Ungermann proposed a patch to improve performance of inplace_solve.
The inplace_solve routine has to cope for 24 different cases:
a) row_major / column_major
b) upper / lower
c) dense / packed / sparse
d) A * x = b / x * A = b
The case row_major / lower_tag / A * x = b is currently mapped to row_major / upper_tag / x * A = b and the case row_major / upper_tag / A * x = b is currently mapped to row_major / lower_tag / x * A = b This is very inefficient for compressed_matrix types! The cases column_major / [lower_tag | upper_tag] / x * A = b are seemingly handled, but I can't get it to complile. The cases of row_major / [lower_tag | upper_tag] / x * A = b *do* have an efficient implementation, which is *not* used to a programming bug, i.e. making the choice of the function depending on the storage type of the vector and not on the matrix.
I rewrote triangular.hpp to
a) handle *all* cases of A * x = b and to
b) "redirect" the x * A = b cases to the aforementioned ones.
This keeps the code about the same size as it currently is. It costs some efficiently for the redirected cases, but previously certain cases were also redirected (just different ones). It is trivial to add the missing cases, but adds quite a bit of code.
old (dense) new (dense) old (sparse) new (sparse) col_low x: 3240000 3240000 10000 10000 row_low x: 5100000 3720000 2590000 10000 col_upp x: 3320000 3340000 10000 10000 row_upp x: 5120000 3750000 2790000 10000 x col_low: - 4660000 - 10000 x row_low: 3330000 4060000 3750000 20000 x col_upp: - 5110000 - 20000 x row_upp: 3230000 3910000 3750000 10000 with dense=ublas::matrix and sparse=ublas::compressed_matrix
- Owner changed from david.bellot to guwi17
- Status changed from new to assigned
- Milestone changed from Boost 1.43.0 to Boost 1.52.0