Critique of "Productivity, Portability, Performance Data-Centric Python" by SCC Team From Sun Yat-sen University

Critique of "Productivity, Portability, Performance Data-Centric Python" by SCC Team From Sun Yat-sen University

In SC21, Ziogas et al. proposed Data-Centric (DaCe) Python. It attains high performance and portability, and further extends the original productivity of Python. This paper analyzes the reproducibility of the DaCe paper as part of the SC22 Student Cluster Competition (SCC). The reproduction experime...

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Veröffentlicht in:IEEE transactions on parallel and distributed systems 2024-02, p.1-4
Hauptverfasser: Huang, Han, Zheng, Tengyang, Yang, Tianxing, Ye, Yang, Liu, Siran, Tang, Zhe, Lu, Shengyou, Feng, Guangnan, Chen, Zhiguang, Huang, Dan
Format: Artikel
Sprache:eng
Schlagworte:
Benchmark testing
Codes
Data-Centric Python
Graphics processing units
Python
Reproducible computation
Runtime
Software
Student Cluster Competition
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Zusammenfassung:In SC21, Ziogas et al. proposed Data-Centric (DaCe) Python. It attains high performance and portability, and further extends the original productivity of Python. This paper analyzes the reproducibility of the DaCe paper as part of the SC22 Student Cluster Competition (SCC). The reproduction experiments are conducted on the Azure CycleCloud. Different from the DaCe paper, we use AMD EPYC 7V73X processors for CPU-based experiments. We successfully reproduce most of the results of the DaCe paper. The remaining results are also explainable.
ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2024.3372291