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| Content Provider | ACM Digital Library |
|---|---|
| Author | Chou, Yuan |
| Abstract | The performance of many important commercial workloads, such as on-line transaction processing, is limited by the frequent stalls due to off-chip instruction and data accesses. These applica- tions are characterized by irregular control flow and complex data access patterns that render many low-cost prefetching schemes, such as stream-based and stride-based prefetching, ineffective. For such applications, correlation-based prefetching, which is ca- pable of capturing complex data access patterns, has been shown to be a more promising approach. However, the large instruction and data working sets of these applications require extremely large correlation tables, making these tables impractical to be im- plemented on-chip. This paper proposes the epoch-based correla- tion prefetcher, which cost-effectively stores its correlation table in main memory and exploits the concept of epochs to hide the long latency of its correlation table access, and which attempts to elim- inate entire epochs instead of individual instruction and data miss- es. Experimental results demonstrate that the epoch-based correlation prefetcher, which requires minimal on-chip real estate to implement, improves the performance of a suite of important commercial benchmarks by 13% to 31% and significantly outper- forms previously proposed correlation prefetchers. |
| Starting Page | 301 |
| Ending Page | 313 |
| Page Count | 13 |
| File Format | |
| ISBN | 0769530478 |
| ISSN | 10724451 |
| DOI | 10.1109/MICRO.2007.23 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2007-12-01 |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Article |
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