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Data prefetching is important for storage system optimization and access performance improvement.
M. Hashemi, K. Swersky, J. Smith, G. Ayers, H. Litz, J. Chang, C. Kozyrakis, and P. Ranganathan, “Learning memory access patterns,” in International Conference on Machine Learning . PMLR, 2018, pp. 1919–1928
1928
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1982
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1991
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J. W. Fu, J. H. Patel, and B. L. Janssens, “Stride directed prefetching in scalar processors,” ACM SIGMICRO Newsletter , vol. 23, no. 1-2, pp. 102–110, 1992
1992
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T.-F. Chen and J.-L. Baer, “Effective hardware-based data prefetching for high-performance processors,” IEEE Transactions on Computers , vol. 44, no. 5, pp. 609–623, 1995
1995
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A. Ki and A. E. Knowles, “Stride prefetching for the secondary data cache,” Journal of Systems Architecture , vol. 46, no. 12, pp. 1093–1102, 2000
2000
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Z. Hu, M. Martonosi, and S. Kaxiras, “Tcp: Tag correlating prefetchers,” in The Ninth International Symposium on High-Performance Computer Architecture, 2003. HPCA-9 2003. Proceedings. IEEE, 2003, pp. 317–326
2003
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Z. Li, Z. Chen, S. M. Srinivasan, Y. Zhou et al. , “C-miner: Mining block correlations in storage systems.” in FAST , vol. 4, 2004, pp. 173–186
2004
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N. Tran and D. A. Reed, “Automatic arima time series modeling for adaptive i/o prefetching,” IEEE Transactions on Parallel and Distributed Systems , vol. 15, no. 4, pp. 362–377, 2004
2004
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K. J. Nesbit and J. E. Smith, “Data cache prefetching using a global history buffer,” in 10th International Symposium on High Performance Computer Architecture (HPCA’04) . IEEE, 2004, pp. 96–96
2004
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C. C. Liu, I. Ganusov, M. Burtscher, and S. Tiwari, “Bridging the processor-memory performance gap with 3d ic technology,” IEEE Design & Test of Computers , vol. 22, no. 6, pp. 556–564, 2005
2005
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S. Somogyi, T. F. Wenisch, A. Ailamaki, B. Falsafi, and A. Moshovos, “Spatial memory streaming,” ACM SIGARCH Computer Architecture News , vol. 34, no. 2, pp. 252–263, 2006
2006
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P. Gu, Y. Zhu, H. Jiang, and J. Wang, “Nexus: a novel weighted-graph-based prefetching algorithm for metadata servers in petabyte-scale storage systems,” in IEEE International Symposium on Cluster Computing & the Grid , 2006
2006
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Y. Chou, “Low-cost epoch-based correlation prefetching for commercial applications,” in 40th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO 2007) . IEEE, 2007, pp. 301–313
2007
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T. F. Wenisch, M. Ferdman, A. Ailamaki, B. Falsafi, and A. Moshovos, “Temporal streams in commercial server applications,” in 2008 IEEE International Symposium on Workload Characterization . IEEE, 2008, pp. 99–108
2008
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F. Scarselli, M. Gori, A. C. Tsoi, M. Hagenbuchner, and G. Monfardini, “The graph neural network model,” IEEE Transactions on Neural Networks , vol. 20, no. 1, pp. 61–80, 2008
2008
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S.-w. Liao, T.-H. Hung, D. Nguyen, C. Chou, C. Tu, and H. Zhou, “Machine learning-based prefetch optimization for data center applications,” in Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis , 2009, pp. 1–10
2009
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——, “Practical off-chip meta-data for temporal memory streaming,” in 2009 IEEE 15th International Symposium on High Performance Computer Architecture . IEEE, 2009, pp. 79–90
2009
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V. Mohan, T. Siddiqua, S. Gurumurthi, and M. R. Stan, “How i learned to stop worrying and love flash endurance.” HotStorage , vol. 10, pp. 3–3, 2010
2010
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H. Kim and U. Ramachandran, “Flashfire: Overcoming the performance bottleneck of flash storage technology,” Georgia Institute of Technology, Tech. Rep., 2010
2010
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S. Boboila and P. Desnoyers, “Performance models of flash-based solid-state drives for real workloads,” in 2011 IEEE 27th Symposium on Mass Storage Systems and Technologies (MSST) . IEEE, 2011, pp. 1–6
2011
Cited alongside, same era.
G. Wu and X. He, “Reducing ssd read latency via nand flash program and erase suspension.” in FAST , vol. 12, 2012, pp. 10–10
2012
Cited alongside, same era.
P. G. Harrison, S. Harrison, N. M. Patel, and S. Zertal, “Storage workload modelling by hidden markov models: Application to flash memory,” Performance Evaluation , vol. 69, no. 1, pp. 17–40, 2012
2012
Cited alongside, same era.
R.-S. Liu, C.-L. Yang, C.-H. Li, and G.-Y. Chen, “Duracache: A durable ssd cache using mlc nand flash,” in Proceedings of the 50th Annual Design Automation Conference , 2013, pp. 1–6
2013
Cited alongside, same era.
M. Bakhshalipour, P. Lotfi-Kamran, and H. Sarbazi-Azad, “Domino temporal data prefetcher,” in 2018 IEEE International Symposium on High Performance Computer Architecture (HPCA) . IEEE, 2018, pp. 131–142
2018
Later among the works it cites.
R. Xu, X. Jin, L. Tao, S. Guo, Z. Xiang, and T. Tian, “An efficient resource-optimized learning prefetcher for solid state drives,” in 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE) . IEEE, 2018, pp. 273–276
2018
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M. Bakhshalipour, M. Shakerinava, P. Lotfi-Kamran, and H. Sarbazi-Azad, “Bingo spatial data prefetcher,” in 2019 IEEE International Symposium on High Performance Computer Architecture (HPCA) . IEEE, 2019, pp. 399–411
2019
Later among the works it cites.
H. Wu, K. Nathella, J. Pusdesris, D. Sunwoo, A. Jain, and C. Lin, “Temporal prefetching without the off-chip metadata,” in Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture , 2019, pp. 996–1008
2019
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A. Jain and C. Lin, “Linearizing irregular memory accesses for improved correlated prefetching,” in Proceedings of the 46th Annual IEEE/ACM International Symposium on Microarchitecture , 2013, pp. 247–259
2013
Cited alongside, same era.
2014
Cited alongside, same era.
B. Perozzi, R. Al-Rfou, and S. Skiena, “Deepwalk: online learning of social representations,” Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining , 2014
2014
Cited alongside, same era.
M. Shevgoor, S. Koladiya, R. Balasubramonian, C. Wilkerson, S. H. Pugsley, and Z. Chishti, “Efficiently prefetching complex address patterns,” in 2015 48th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO) . IEEE, 2015, pp. 141–152
2015
Cited alongside, same era.
J. Liao, F. Trahay, B. Gerofi, and Y. Ishikawa, “Prefetching on storage servers through mining access patterns on blocks,” IEEE Transactions on Parallel and Distributed Systems , vol. 27, no. 9, pp. 2698–2710, 2015
2015
Cited alongside, same era.
L. Peled, S. Mannor, U. Weiser, and Y. Etsion, “Semantic locality and context-based prefetching using reinforcement learning,” in 2015 ACM/IEEE 42nd Annual International Symposium on Computer Architecture (ISCA) . IEEE, 2015, pp. 285–297
2015
Cited alongside, same era.
2015
Cited alongside, same era.
A. Laga, J. Boukhobza, M. Koskas, and F. Singhoff, “Lynx: A learning linux prefetching mechanism for ssd performance model,” in 2016 5th Non-Volatile Memory Systems and Applications Symposium (NVMSA) . IEEE, 2016, pp. 1–6
2016
Cited alongside, same era.
Later among the works it cites.
H. Wu, K. Nathella, D. Sunwoo, A. Jain, and C. Lin, “Efficient metadata management for irregular data prefetching,” in 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA) . IEEE, 2019, pp. 1–13
2019
Later among the works it cites.
L. Peled, U. Weiser, and Y. Etsion, “A neural network prefetcher for arbitrary memory access patterns,” ACM Transactions on Architecture and Code Optimization (TACO) , vol. 16, no. 4, pp. 1–27, 2019
2019
Later among the works it cites.
C. Zhang, D. Song, C. Huang, A. Swami, and N. V. Chawla, “Heterogeneous graph neural network,” in Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining , 2019, pp. 793–803
2019
Later among the works it cites.
S. Wu, Y. Tang, Y. Zhu, L. Wang, X. Xie, and T. Tan, “Session-based recommendation with graph neural networks,” in Proceedings of the AAAI Conference on Artificial Intelligence , 2019, pp. 346–353
2019
Later among the works it cites.
C. Chakraborttii and H. Litz, “Learning i/o access patterns to improve prefetching in ssds,” ICML-PKDD , 2020
2020
Later among the works it cites.
Q. Shi, J. Yin, J. Cai, A. Cichocki, T. Yokota, L. Chen, M. Yuan, and J. Zeng, “Block hankel tensor arima for multiple short time series forecasting,” in Proceedings of the AAAI Conference on Artificial Intelligence , vol. 34, 2020, pp. 5758–5766
2020
Later among the works it cites.
G. O. Ganfure, C.-F. Wu, Y.-H. Chang, and W.-K. Shih, “Deepprefetcher: A deep learning framework for data prefetching in flash storage devices,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems , vol. 39, no. 11, pp. 3311–3322, 2020
2020
Later among the works it cites.
Z. Wu, S. Pan, F. Chen, G. Long, C. Zhang, and S. Y. Philip, “A comprehensive survey on graph neural networks,” IEEE Transactions on Neural Networks and Learning Systems , vol. 32, no. 1, pp. 4–24, 2020
2020
Later among the works it cites.
2020
Later among the works it cites.
2021
Later among the works it cites.
Y. Chen, Y. Zhang, J. Wu, J. Wang, and C. Xing, “Revisiting data prefetching for database systems with machine learning techniques,” in 2021 IEEE 37th International Conference on Data Engineering (ICDE) . IEEE, 2021, pp. 2165–2170
2021
Later among the works it cites.
H. Zhou, S. Zhang, J. Peng, S. Zhang, J. Li, H. Xiong, and W. Zhang, “Informer: Beyond efficient transformer for long sequence time-series forecasting,” in Proceedings of AAAI , 2021
2021
Later among the works it cites.
Z. Shi, A. Jain, K. Swersky, M. Hashemi, P. Ranganathan, and C. Lin, “A hierarchical neural model of data prefetching,” in Proceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems , 2021, pp. 861–873
2021
Later among the works it cites.
G.-S. Xie, J. Liu, H. Xiong, and L. Shao, “Scale-aware graph neural network for few-shot semantic segmentation,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2021, pp. 5475–5484
2021
Later among the works it cites.
X. Li, Q. Shi, G. Hu, L. Chen, H. Mao, Y. Yang, M. Yuan, J. Zeng, and Z. Cheng, “Block access pattern discovery via compressed full tensor transformer,” in CIKM , 2021
2021
Later among the works it cites.