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CCS: A Motif-Based Storage Format for Micro-execution Dependence Graph

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Advanced Parallel Processing Technologies (APPT 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14103))

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Abstract

Micro-execution dependence graphs model the program execution on a microprocessor as relationships of micro-execution events intra- and inter-instructions for performance analysis. Each instruction constitutes a motif whose structure is defined by the dependence graph model. With the size of the application increasing dramatically, storing a large-scale dependence graph with billions of instructions becomes difficult. However, popular graph storage formats, such as CSR and CSC, are inefficient for motifs. And the current motif-based compression methods involve the time-consuming process of subgraph isomorphism checking, which is NP-hard. To reduce redundancy, we propose a novel motif-based lossless storage format called compressed common subgraph (CCS) for micro-execution dependence graphs. The key idea is to divide the graph into the intra- and inter-motif parts and compress the common subgraph structures in the intra-motif part by storing the same structures only once. Our method avoids subgraph isomorphism checking because the motifs (instructions) are regularly arranged. Furthermore, the CCS format has two variant implementations, compressed common single subgraph (CCSS) and compressed common multiple subgraphs (CCMS) to adapt to various dependence graph models. Experimental results show that our CCSS and CCMS formats use 16.66% and 8.67% less memory size than the CSC graph format, respectively.

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Acknowledgements

This work is supported by the National Key Research and Development Program of China (under Grant 2022YFB3105103).

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Authors and Affiliations

  1. State Key Lab of Processors, ICT, CAS, Beijing, China

    Yawen Zheng, Chenji Han & Jian Wang

  2. Institute of Computing Technology, CAS, Beijing, China

    Yawen Zheng, Chenji Han, Tingting Zhang & Jian Wang

  3. University of Chinese Academy of Sciences, Beijing, China

    Yawen Zheng, Chenji Han & Jian Wang

  4. Loongson Technology Corporation Limited, Beijing, China

    Tingting Zhang

  5. Electric Power Research Institute of State Grid Liaoning Electric Power Co., Ltd., Shenyang, China

    Chao Yang

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  1. Yawen Zheng
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  2. Chenji Han
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  5. Jian Wang
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Corresponding author

Correspondence to Yawen Zheng .

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Editors and Affiliations

  1. Shanghai Jiao Tong University, Shanghai, China

    Chao Li

  2. Tsinghua University, Beijing, Beijing, China

    Zhenhua Li

  3. National University of Defense Technology, Nanjing, China

    Li Shen

  4. Shanghai Jiao Tong University, Shanghai, China

    Fan Wu

  5. Nankai University, Tianjin, China

    Xiaoli Gong

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Zheng, Y., Han, C., Zhang, T., Yang, C., Wang, J. (2024). CCS: A Motif-Based Storage Format for Micro-execution Dependence Graph. In: Li, C., Li, Z., Shen, L., Wu, F., Gong, X. (eds) Advanced Parallel Processing Technologies. APPT 2023. Lecture Notes in Computer Science, vol 14103. Springer, Singapore. https://doi.org/10.1007/978-981-99-7872-4_8

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  • DOI: https://doi.org/10.1007/978-981-99-7872-4_8

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