GroupUCP: An On-Demand Fine-Grained Cache Dynamic Partition Strategy

Zhang Chuanqi; Wang Sa; Sun Ninghui; Bao Yungang

doi:10.7544/issn1000-1239.202440061

Journal of Computer Research and Development > 2025 > 62(4): 989-1002. > DOI: 10.7544/issn1000-1239.202440061 CSTR: 32373.14.issn1000-1239.202440061

Zhang Chuanqi, Wang Sa, Sun Ninghui, Bao Yungang. GroupUCP: An On-Demand Fine-Grained Cache Dynamic Partition Strategy[J]. Journal of Computer Research and Development, 2025, 62(4): 989-1002. DOI: 10.7544/issn1000-1239.202440061

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GroupUCP: An On-Demand Fine-Grained Cache Dynamic Partition Strategy

Zhang Chuanqi^{1, 2, 3,},
Wang Sa^{1, 2, ,},
Sun Ninghui^{1, 2, 3},
Bao Yungang^{1, 2, 3}

1.
State Key Lab of Processors (Institute of Computing Technology, Chinese Academy of Sciences), Beijing 100190
2.
School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing 101408
3.
Beijing Institute of Open Source Chip, Beijing 100080

Funds: This work was supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDA0320000, XDA0320300), the National Natural Science Foundation of China (62090022, 62172388), and the Science and Technology Project of State Grid Corporation of China (SGJSXT00TYJS2100414).

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Author Bio:
Zhang Chuanqi: born in 1996. PhD candidate. Student member of CCF. His main research interest includes data center computer architecture

Wang Sa: born in 1986. PhD, associate professor. Member of CCF. His main research interests include cloud computing, operating systems, and system modeling and performance analysis

Sun Ninghui: born in 1968. PhD. Academician of Chinese Academy of Engineering. Fellow of CCF. His main research interests include computer architecture and high performance computing

Bao Yungang: born in 1980. PhD, professor. Member of CCF. His main research interests include datacenter architecture, agile design methodology of processor chips, and ecosystem of open-source processor chips
Received Date: January 28, 2024
Revised Date: July 18, 2024
Accepted Date: September 02, 2024
Available Online: September 08, 2024

Graphical Abstract

Abstract

Abstract

With the advancement of modern computer technology, the memory wall problem is getting more and more severe. Under this background, the last-level cache in multi-level memory hierarchy becomes a key resource affecting system performance. In recent years, various researches have optimized the last-level cache by means of size expansion and dynamic resource management. Way-partitioning technique is the main method of cache resource management, which optimizes system performance by partitioning the cache into ways and allocating them to each application. However, it is coarse-grained and requires all sets of caches to follow the same way-partitioning strategy. In fact, applications may have different space demand on different sets, and the way-partitioning technique restricts the space utilization of the cache, resulting in a waste of cache resources. In this paper, we propose an on-demand fine-grained cache resource management technique, GroupUCP, whose design idea is to aggregate individual cache sets into groups based on the different space demand of each application on each set, using dynamic grouping and real-time evaluation. Each group can be allocated space on demand independently, thus improving cache utilization and overall system performance. Experiments demonstrate that GroupUCP achieves finer-grained on-demand resource allocation using less hardware resources than the traditional UCP approach and achieves higher system performance improvement in cache-sensitive application combinations which shows imbalance space demand of cache.
- multi-core processor,
- shared cache,
- dynamic partitioning,
- dynamic group,
- metadata compression

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References (49)

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