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Update Setting up diagonalization engine authored by Gabriel Wlazłowski's avatar Gabriel Wlazłowski
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Setting-up-diagonalization-engine.md
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It is recommended to use `PZHEEVR`. This engine takes advantage from the fact that typically we extract only a fraction of eigenstates. However, we find that in some rare cases (system dependent) this routine does not work correctly. In such a case, `PZHEEVD` should be used.
# Benchmarks
# Benchmarks & Scalings
| matrix size | p | q | mb | nb | prec. | routine | system | time [sec] | cost |
| ------------|---|---|----|----|--------|---------|--------|------------|------|
| **65,536 = 2x32^3** | 24 | 28 | 8 | 8 | complex| ELPA (1-GPU) | Summit | **118** | **0.52 nh** |
......@@ -63,3 +63,7 @@ It is recommended to use `PZHEEVR`. This engine takes advantage from the fact th
(1-GPU): `ELPA_SOLVER_1STAGE`, `ELPA_2STAGE_COMPLEX_GPU` or `ELPA_2STAGE_REAL_GPU`
(2-GPU): `ELPA_SOLVER_2STAGE`, `ELPA_2STAGE_COMPLEX_GPU` or `ELPA_2STAGE_REAL_GPU`
(2-CPU): `ELPA_SOLVER_2STAGE`, `ELPA_2STAGE_COMPLEX_DEFAULT` or `ELPA_2STAGE_REAL_DEFAULT`
## Plots
These scalings are derived empirically.
![summit-scaling](uploads/902dbf6ba1829c28d250bc105ffc35cf/summit-scaling.png)
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