High performance computing power is important for the current advanced calculations of scientific applications. A multiprocessor system obtains its high performance from the fact that some computations can proceed in parallel. A parallelizing compiler can take a sequential program as input and automatically translate it into parallel form for the target multiprocessor system. But when loops with arrays of irregular, nonlinear or dynamic access patterns, no any current parallelizing compiler can determine whether data dependences exist at compile-time. Thus a run-time parallel algorithm will be utilized to determine dependences and extract the potential parallelism of loops. In this thesis, we propose an efficient run-time parallelization technique to compute a proper parallel execution schedule in those loops. This new method first detects immediate predecessor iterations of each loop iteration and constructs an immediate predecessor table, then efficiently schedules the whole loop iterations into wavefronts for parallel execution. According to either theoretical analysis or experimental results, our new run-time parallelization technique reveals high speedup and low processing overhead. Furthermore, this new technique is appropriate to implement on multiprocessor systems due to the characteristics of high scalability.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0706100-132843 |
| Date | 06 July 2000 |
| Creators | Wu, Chi-Fan |
| Contributors | Ting-Wei Hou, Tsung-Chuan Huang, Tse-Sheng Chen, John Y. Chiang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0706100-132843 |
| Rights | unrestricted, Copyright information available at source archive |
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