- AutorIn
- Mohammad Izadi
- Titel
- Hierarchical Matrix Techniques on Massively Parallel Computers
- Untertitel
- Hierarchisches Matrix-Techniken fuer Massiv Parallele Computer
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:15-qucosa-101164
- Datum der Einreichung
- 16.07.2012
- Datum der Verteidigung
- 12.04.2012
- Abstract (EN)
- Hierarchical matrix (H-matrix) techniques can be used to efficiently treat dense matrices. With an H-matrix, the storage requirements and performing all fundamental operations, namely matrix-vector multiplication, matrix-matrix multiplication and matrix inversion can be done in almost linear complexity. In this work, we tried to gain even further speedup for the H-matrix arithmetic by utilizing multiple processors. Our approach towards an H-matrix distribution relies on the splitting of the index set. The main results achieved in this work based on the index-wise H-distribution are: A highly scalable algorithm for the H-matrix truncation and matrix-vector multiplication, a scalable algorithm for the H-matrix matrix multiplication, a limited scalable algorithm for the H-matrix inversion for a large number of processors.
- Freie Schlagwörter (DE)
- Hierarchische Matrizen, parallelen Algorithmus,Distributed-Memory-Systeme
- Freie Schlagwörter (EN)
- Hierarchical matrices, parallel algorithm, Distributed-Memory-System
- Klassifikation (DDC)
- 000
- GutachterIn
- Prof. Dr. Gerhard Zumbusch
- BetreuerIn
- Prof. Dr. Dre. h.c. Wolfgang Hackbusch
- Den akademischen Grad verleihende / prüfende Institution
- Max Planck Institute for Mathematics in the Sciences (MIS), Leipzig
- URN Qucosa
- urn:nbn:de:bsz:15-qucosa-101164
- Veröffentlichungsdatum Qucosa
- 11.12.2012
- Dokumenttyp
- Dissertation
- Sprache des Dokumentes
- Englisch