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| Content Provider | ACM Digital Library |
|---|---|
| Author | Wenisch, Thomas F. Ailamaki, Anastasia Somogyi, Stephen Falsafi, Babak |
| Abstract | Recent research advocates memory streaming techniques to alleviate the performance bottleneck caused by the high latencies of off-chip memory accesses. Temporal memory streaming replays previously observed miss sequences to eliminate long chains of dependent misses. Spatial memory streaming predicts repetitive data layout patterns within fixed-size memory regions. Because each technique targets a different subset of misses, their effectiveness varies across workloads and each leaves a significant fraction of misses unpredicted. In this paper, we propose Spatio-Temporal Memory Streaming (STeMS) to exploit the synergy between spatial and temporal streaming. We observe that the order of spatial accesses repeats both within and across regions. STeMS records and replays the temporal sequence of region accesses and uses spatial relationships within each region to dynamically reconstruct a predicted total miss order. Using trace-driven and cycle-accurate simulation across a suite of commercial workloads, we demonstrate that with similar implementation complexity as temporal streaming, STeMS achieves equal or higher coverage than spatial or temporal memory streaming alone, and improves performance by 31%, 3%, and 18% over stride, spatial, and temporal prediction, respectively. |
| Starting Page | 69 |
| Ending Page | 80 |
| Page Count | 12 |
| File Format | |
| ISSN | 01635964 |
| DOI | 10.1145/1555815.1555766 |
| Journal | ACM SIGARCH Computer Architecture News (CARN) |
| Volume Number | 37 |
| Issue Number | 3 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 1981-04-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Prefetching Temporal correlation Spatial correlation |
| Content Type | Text |
| Resource Type | Article |
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