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Exploring Core and Cache Hierarchy Bottlenecks in Graph Processing Workloads., , , , and . IEEE Comput. Archit. Lett., 17 (2): 197-200 (2018)Persistence Parallelism Optimization: A Holistic Approach from Memory Bus to RDMA Network., , , , , and . MICRO, page 494-506. IEEE Computer Society, (2018)Alleviating Irregularity in Graph Analytics Acceleration: a Hardware/Software Co-Design Approach., , , , , , , , , and 4 other author(s). MICRO, page 615-628. ACM, (2019)Rubik: A Hierarchical Architecture for Efficient Graph Learning., , , , , , , , , and 2 other author(s). CoRR, (2020)Analysis and Optimization of the Memory Hierarchy for Graph Processing Workloads., , , , , , , and . HPCA, page 373-386. IEEE, (2019)Rubik: A Hierarchical Architecture for Efficient Graph Neural Network Training., , , , , , , , , and 1 other author(s). IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 41 (4): 936-949 (2022)Improving Streaming Graph Processing Performance using Input Knowledge., , , , , , and . MICRO, page 1036-1050. ACM, (2021)SpaceA: Sparse Matrix Vector Multiplication on Processing-in-Memory Accelerator., , , , , , , and . HPCA, page 570-583. IEEE, (2021)SAGA-Bench: Software and Hardware Characterization of Streaming Graph Analytics Workloads., , , , , , and . ISPASS, page 12-23. IEEE, (2020)