Name
Abstract | ||
|---|---|---|
Exploiting memory level parallelism (MLP) is crucial to hide long memory and last level cache access latencies. While out-of-order (OoO) cores, and techniques building on them, are effective at exploiting MLP, they deliver poor energy efficiency due to their complex hardware and the resulting energy overheads. As energy efficiency becomes the prime design constraint, we investigate low complexity/energy mechanisms to exploit MLP.This work revisits slice-out-of-order (sOoO) cores as an energy efficient alternative to OoO cores for MLP exploitation. These cores construct slices of MLP generating instructions and execute them out-of-order with respect to the rest of instructions. However, the slices and the remaining instructions, by themselves, execute in-order. Though their energy overhead is low compared to full OoO cores, sOoO cores fall considerably behind in terms of MLP extraction. We observe that their dependence-oblivious inorder slice execution causes dependent slices to frequently block MLP generation.To boost MLP generation in sOoO cores, we introduce Freeway, a sOoO core based on a new dependence-aware slice execution policy that tracks dependent slices and keeps them out of the way of MLP extraction. The proposed core incurs minimal area and power overheads, yet approaches the MLP benefits of fully OoO cores. Our evaluation shows that Freeway outperforms the state-of-the-art sOoO core by 12% and is within 7% of the MLP limits of full OoO execution. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/HPCA.2019.00009 | 2019 IEEE International Symposium on High Performance Computer Architecture (HPCA) |
Keywords | Field | DocType |
Out of order,Traffic control,Hardware,Complexity theory,Memory management,Performance gain,Parallel processing | Computer science,Parallel computing,Parallel processing,Memory management,Out-of-order execution | Conference |
ISSN | ISBN | Citations |
1530-0897 | 978-1-7281-1444-6 | 4 |
PageRank | References | Authors |
0.38 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rakesh Kumar | 1 | 22 | 3.62 |
| Mehdi Alipour | 2 | 20 | 3.40 |
| David Black-Schaffer | 3 | 266 | 23.20 |