Reproducing Performance of Data-Centric Python by SCC Team From National Tsing Hua University

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Fu-Chiang Chang, En-Ming Huang, Pin-Yi Kuo, Chan-Yu Mou, Hsu-Tzu Ting, Pang-Ning Wu, Jerry Chou

Published: 2025, Last Modified: 02 Mar 2026IEEE Trans. Parallel Distributed Syst. 2025EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: As part of the Student Cluster Competition at the SC22 conference, this work aims to reproduce the performance evaluations of the Data Centric (DaCe) Python framework by leveraging Intel MKL and NVIDIA CUDA interface. The evaluations are conducted on a single CPU-based node, NVIDIA A100 GPUs, and an eight-node cloud supercomputer. Our experimental results successfully reproduce the performance evaluations on our cluster. Additionally, we provide insightful analysis and propose effective methods for achieving higher performance when utilizing DaCe as an acceleration library.