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Performance Characterization of Multi-threaded Graph Processing Applications on Intel Many-Integrated-Core Architecture., , and . CoRR, (2017)A TSQR Based Krylov Basis Computation Method on Hybrid GPU Cluster., and . CLUSTER, page 106-109. IEEE Computer Society, (2015)SubGraph2Vec: Highly-Vectorized Tree-like Subgraph Counting., , , , , , , , and . IEEE BigData, page 483-492. IEEE, (2019)Performance Characterization of Multi-threaded Graph Processing Applications on Many-Integrated-Core Architecture., , and . ISPASS, page 199-208. IEEE Computer Society, (2018)Toward Auto-tuned Krylov Basis Computation for Different Sparse Matrix Formats and Interconnects on GPU Clusters., and . CLUSTER, page 537-538. IEEE Computer Society, (2015)Benchmarking Harp-DAAL: High Performance Hadoop on KNL Clusters., , , , , , , , , and 3 other author(s). CLOUD, page 82-89. IEEE Computer Society, (2017)High-Performance Massive Subgraph Counting using Pipelined Adaptive-Group Communication., , , , , , and . CoRR, (2018)PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender Systems., , , , , , , , , and 5 other author(s). ICDE, page 3453-3466. IEEE, (2022)HarpGBDT: Optimizing Gradient Boosting Decision Tree for Parallel Efficiency., , , , , , , , , and . CLUSTER, page 1-11. IEEE, (2019)HarpLDA+: Optimizing latent dirichlet allocation for parallel efficiency., , , , , , , , , and 2 other author(s). IEEE BigData, page 243-252. IEEE Computer Society, (2017)