Tagged Geometric History Length Access Interval Prediction for Tightly Coupled Memory Systems

Author:

Razilov Viktor,Wittig Robert,Matúš Emil,Fettweis Gerhard

Publisher

Springer International Publishing

Reference17 articles.

1. Haas, S., et al.: A heterogenous SDR MPSoC in 28 nm CMOS for low-latency wireless applications. In: DAC. ACM Press, New York (2017). https://doi.org/10.1145/3061639.3062188

2. Lecture Notes in Computer Science;R Wittig,2019

3. Wittig, R., Hasler, M., Matus, E., Fettweis, G.: Statistical access interval prediction for tightly coupled memory systems. In: COOL CHIPS. IEEE (2019). https://doi.org/10.1109/CoolChips.2019.8721304

4. Mittal, S.: A survey of techniques for dynamic branch prediction. Concurr. Comput. Pract. Exp. 31(1), 1–36 (2018)

5. Seznec, A., Michaud, P.: A case for (partially) TAgged GEometric history length branch prediction. J. Instruct. Level Parall. 8 (2006). https://www.jilp.org/vol8

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Access Interval Prediction by Partial Matching for Tightly Coupled Memory Systems;International Journal of Parallel Programming;2024-02-13

2. Enlarging the Time Budget for Neural Network Based Predictors for Access Interval Prediction;2024 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA);2024-02-01

3. Access Interval Prediction with Neural Networks for Tightly Coupled Memory Systems;2023 26th Euromicro Conference on Digital System Design (DSD);2023-09-06

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