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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ling Shang Petiton, S. Hugues, M. |
| Copyright Year | 2009 |
| Abstract | Two kinds of parallel possibilities which are intrastep and inter-steps parallelism exist in the block-based Gauss-Jordan algorithm which is a classical method of large scale matrix inversion. But the existing parallel paradigm of Block-based Gauss-Jordan algorithm just aiming at the intra-step parallelism, can’t meet the requirement of making more tasks executed simultaneously in high performance platform can be harnessed more and more computing resources. To overcome the problem described above, this paper presents a hybrid parallel paradigm exploiting all the possible parallelizable parts of the Gauss-Jordan algorithm. In this hybrid parallel paradigm, 1) Divide and conquer paradigm is responsible for decomposing the large granularity task into sub-tasks as much as possible; 2) Single program multi data (SPMD) paradigm deals with intra-step parallelism in the algorithm; 3) Data pipelining paradigm helps to solve the problem of inter-steps parallelism. Finally some experiments based on comparison the hybrid parallel paradigm with the existing parallel paradigm show us the good performance of our paradigm. |
| Starting Page | 193 |
| Ending Page | 200 |
| File Size | 652730 |
| Page Count | 8 |
| File Format | |
| ISBN | 9780769537665 |
| DOI | 10.1109/GCC.2009.75 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-08-27 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Gauss-Jordan algorithm parallel paradigm parallelism Pipeline processing Concurrent computing Parallel programming High performance computing Gaussian processes Parallel processing Grid computing Iterative algorithms Large-scale systems data dependence |
| Content Type | Text |
| Resource Type | Article |
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