Efficient Index Generation for Compiling Two-Level Mappings in Data-Parallel Programs
| Autor: | Kuei-Ping Shih, Chua-Huang Huang, Chih-Yung Chang, Jang-Ping Sheu |
|---|---|
| Rok vydání: | 2000 |
| Předmět: |
Computer Networks and Communications
Fortran Computer science Locality Parallel computing Theoretical Computer Science Artificial Intelligence Hardware and Architecture Compression (functional analysis) Table (database) Distributed memory computer Algorithm Software computer.programming_language Data compression High Performance Fortran Block (data storage) |
| Zdroj: | Journal of Parallel and Distributed Computing. 60:189-216 |
| ISSN: | 0743-7315 |
| DOI: | 10.1006/jpdc.1999.1601 |
| Popis: | This paper presents compilation techniques used to compress holes, which are caused by the nonunit alignment stride in a two-level data-processor mapping. Holes are the memory locations mapped by useless template cells. To fully utilize the memory space, memory holes should be removed. In a two-level data-processor mapping, there is a repetitive pattern for array elements mapped onto processors. We classify blocks into classes and use a class table to record the distribution of each class in the first repetitive data distribution pattern. Similarly, data distribution on a processor also has a repetitive pattern. We use a compression table to record the distribution of each block in the first repetitive data distribution pattern on a processor. By using a class table and a compression table, hole compression can be easily and efficiently achieved. Compressing holes can save memory usage, improve spatial locality and further improve system performance. The proposed method is efficient, stable, and easy to implement. The experimental results do confirm the advantages of our proposed method over existing methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect