Data-driven Science - 2023

Chen, Z., Zhang, F., Guan, J. W., Zhai, J., Shen, X., Zhang, H., … Du, X. (2023). CompressGraph: Efficient Parallel Graph Analytics with Rule-Based Compression. Proceedings of the ACM on Management of Data. https://doi.org/10.1145/3588684

Chen, J.-A., Sung, H.-H., Shen, X., Choudhury, S., & Li, A. (2023). BitGNN: Unleashing the Performance Potential of Binary Graph Neural Networks on GPUs. PROCEEDINGS OF THE 37TH INTERNATIONAL CONFERENCE ON SUPERCOMPUTING, ACM ICS 2023, pp. 264–276. https://doi.org/10.1145/3577193.3593725

Ye, C., Xu, Y., Shen, X., Sha, Y., Liao, X., Jin, H., & Solihin, Y. (2023). SpecPMT: Speculative Logging for Resolving Crash Consistency Overhead of Persistent Memory. PROCEEDINGS OF THE 28TH ACM INTERNATIONAL CONFERENCE ON ARCHITECTURAL SUPPORT FOR PROGRAMMING LANGUAGES AND OPERATING SYSTEMS, VOL 2, ASPLOS 2023, pp. 762–777. https://doi.org/10.1145/3575693.3575696

Zhang, F., Wu, R., Guan, J., Zheng, Z., Guo, X., Zhang, X., … Shen, X. (2023). Expanding the Edge: Enabling Efficient Winograd CNN Inference With Deep Reuse on Edge Device. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 35(10), 10181–10196. https://doi.org/10.1109/TKDE.2023.3269017

Ye, C., Xu, Y., Shen, X., Sha, Y., Liao, X., Jin, H., & Solihin, Y. (2023). Reconciling Selective Logging and Hardware Persistent Memory Transaction. 2023 IEEE INTERNATIONAL SYMPOSIUM ON HIGH-PERFORMANCE COMPUTER ARCHITECTURE, HPCA, pp. 664–676. https://doi.org/10.1109/HPCA56546.2023.10071088

Chen, J.-A., Sung, H.-H., Shen, X., Tallent, N., Barker, K., & Li, A. (2023). Accelerating matrix-centric graph processing on GPUs through bit-level optimizations. JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 177, 53–67. https://doi.org/10.1016/j.jpdc.2023.02.013

Zhang, G., Mariano, B., Shen, X., & Dillig, I. (2023). Automated Translation of Functional Big Data similar to eries to SQL. PROCEEDINGS OF THE ACM ON PROGRAMMING LANGUAGES-PACMPL, 7(OOPSLA). https://doi.org/10.1145/3586047

Chen, J.-A., Niu, W., Ren, B., Wang, Y., & Shen, X. (2023). Survey: Exploiting Data Redundancy for Optimization of Deep Learning. ACM COMPUTING SURVEYS, 55(10). https://doi.org/10.1145/3564663