IEICE TRANSACTIONS on Information
PMOP: Efficient Per-Page Most-Offset Prefetcher
Summary :
Hardware prefetching involves a sophisticated balance between accuracy, coverage, and timeliness while minimizing hardware cost. Recent prefetchers have achieved these goals, but they still require complex hardware and a significant amount of storage. In this paper, we propose an efficient Per-page Most-Offset Prefetcher (PMOP) that minimizes hardware cost and simultaneously improves accuracy while maintaining coverage and timeliness. We achieve these objectives using an enhanced offset prefetcher that performs well with a reasonable hardware cost. Our approach first addresses coverage and timeliness by allowing multiple Most-Offset predictions. To minimize offset interference between pages, the PMOP leverages a fine-grain per-page offset filter. This filter records the access history with page-IDs, which enables efficient mapping and tracking of multiple offset streams from diverse pages. Analysis results show that PMOP outperforms the state-of-the-art Signature Path Prefetcher while reducing storage overhead by a factor of 3.4.
- Publication
- IEICE TRANSACTIONS on Information Vol.E102-D No.7 pp.1271-1279
- Publication Date
- 2019/07/01
- Publicized
- 2019/04/12
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2018EDP7328
- Type of Manuscript
- PAPER
- Category
- Computer System
Authors
Kanghee KIM
Inha University
Wooseok LEE
University of Texas at Austin
Sangbang CHOI
Inha University
Keyword
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Kanghee KIM, Wooseok LEE, Sangbang CHOI, "PMOP: Efficient Per-Page Most-Offset Prefetcher" in IEICE TRANSACTIONS on Information,
vol. E102-D, no. 7, pp. 1271-1279, July 2019, doi: 10.1587/transinf.2018EDP7328.
Abstract: Hardware prefetching involves a sophisticated balance between accuracy, coverage, and timeliness while minimizing hardware cost. Recent prefetchers have achieved these goals, but they still require complex hardware and a significant amount of storage. In this paper, we propose an efficient Per-page Most-Offset Prefetcher (PMOP) that minimizes hardware cost and simultaneously improves accuracy while maintaining coverage and timeliness. We achieve these objectives using an enhanced offset prefetcher that performs well with a reasonable hardware cost. Our approach first addresses coverage and timeliness by allowing multiple Most-Offset predictions. To minimize offset interference between pages, the PMOP leverages a fine-grain per-page offset filter. This filter records the access history with page-IDs, which enables efficient mapping and tracking of multiple offset streams from diverse pages. Analysis results show that PMOP outperforms the state-of-the-art Signature Path Prefetcher while reducing storage overhead by a factor of 3.4.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2018EDP7328/_p
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@ARTICLE{e102-d_7_1271,
author={Kanghee KIM, Wooseok LEE, Sangbang CHOI, },
journal={IEICE TRANSACTIONS on Information},
title={PMOP: Efficient Per-Page Most-Offset Prefetcher},
year={2019},
volume={E102-D},
number={7},
pages={1271-1279},
abstract={Hardware prefetching involves a sophisticated balance between accuracy, coverage, and timeliness while minimizing hardware cost. Recent prefetchers have achieved these goals, but they still require complex hardware and a significant amount of storage. In this paper, we propose an efficient Per-page Most-Offset Prefetcher (PMOP) that minimizes hardware cost and simultaneously improves accuracy while maintaining coverage and timeliness. We achieve these objectives using an enhanced offset prefetcher that performs well with a reasonable hardware cost. Our approach first addresses coverage and timeliness by allowing multiple Most-Offset predictions. To minimize offset interference between pages, the PMOP leverages a fine-grain per-page offset filter. This filter records the access history with page-IDs, which enables efficient mapping and tracking of multiple offset streams from diverse pages. Analysis results show that PMOP outperforms the state-of-the-art Signature Path Prefetcher while reducing storage overhead by a factor of 3.4.},
keywords={},
doi={10.1587/transinf.2018EDP7328},
ISSN={1745-1361},
month={July},}
Copy
TY - JOUR
TI - PMOP: Efficient Per-Page Most-Offset Prefetcher
T2 - IEICE TRANSACTIONS on Information
SP - 1271
EP - 1279
AU - Kanghee KIM
AU - Wooseok LEE
AU - Sangbang CHOI
PY - 2019
DO - 10.1587/transinf.2018EDP7328
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E102-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2019
AB - Hardware prefetching involves a sophisticated balance between accuracy, coverage, and timeliness while minimizing hardware cost. Recent prefetchers have achieved these goals, but they still require complex hardware and a significant amount of storage. In this paper, we propose an efficient Per-page Most-Offset Prefetcher (PMOP) that minimizes hardware cost and simultaneously improves accuracy while maintaining coverage and timeliness. We achieve these objectives using an enhanced offset prefetcher that performs well with a reasonable hardware cost. Our approach first addresses coverage and timeliness by allowing multiple Most-Offset predictions. To minimize offset interference between pages, the PMOP leverages a fine-grain per-page offset filter. This filter records the access history with page-IDs, which enables efficient mapping and tracking of multiple offset streams from diverse pages. Analysis results show that PMOP outperforms the state-of-the-art Signature Path Prefetcher while reducing storage overhead by a factor of 3.4.
ER -
English
