Name
Abstract | ||
|---|---|---|
hi this paper we introduce a page-based Lazy Release Consistency protocol called ADSM that constantly and efficiently adapts to the applications' sharing patterns. Adaptation in ADSM is based on our dynamic categorization of the type of sharing experienced by each page. Pages car? be categorized as falsely-shared, migratory, or producer/consumer(s). Migratory, and producer/consumer(s) pages are managed in single-writer mode, while falsely-shared data are managed in multiple-writer mode. Coherence is kept with invalidations for most types of the shared data, but updates are used for lock-protected data in migratory state and barrier-protected data in pro ducer/consumer(s) state. We performed experiments with 6 parallel applications on an 8-node SP2 system, comparing our protocol against standard TreadMarks and a version of TreadMarks that also adapts to sharing patterns. Our results show that ADSM consistently outperforms its competitors; our protocol can improve the TreadMarks speedups by as much as 155%, while surpassing the performance of the adaptive TreadMarks implementation by as much as 67%. Our main conclusions are that our categorization and adaptation strategies are useful techniques for improving the performance of page-based software DSMs, while ADSM is a highly-efficient option for low-cost parallel computing. |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1109/HPCA.1998.650568 | HPCA |
Keywords | Field | DocType |
parallel computing,software performance,workstations,operating systems,application software,treadmarks,merging,parallel computer,performance,protocols | Computer science,Real-time computing,Software performance testing,Software,Application software,Electrical capacitance tomography,Distributed computing,Categorization,Parallel computing,Workstation,TreadMarks,Operating system,Release consistency | Conference |
ISBN | Citations | PageRank |
0-8186-8323-6 | 39 | 1.72 |
References | Authors | |
15 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luiz Rodolpho Monnerat | 1 | 39 | 1.72 |
| Ricardo Bianchini | 2 | 2706 | 172.32 |