Peachy Parallel Assignments (EduHPC 2023)
Peachy Parallel Assignments (EduHPC 2023)
复制标题
完美的并行作业 (EduHPC 2023)
DOI：
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
David P. Bunde
中科院分区：
文献类型：
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作者：
H. M. Bücker;Jeremiah Corrado;Daniel Fedorin;Diego Garcia;Arturo González;John Li;Maria Pantoja;Erik Pautsch;Marieke Plesske;Marcelo Ponce;Silvio Rizzi;Erik Saule;Johannes Schoder;G. Thiruvathukal;Ramses Van Zon;Wolf Weber;David P. Bunde
Peachy并行计算是用于教授并行计算概念的模型作业。他们是竞争性选择被其他教师采用和“酷和鼓舞人心的”学生。因此，他们允许教师轻松地添加高质量的作业，将吸引学生到他们的课堂。这组Peachy作业包含六个新作业。完成这些课程的学生将使用k-Nearest Neighbor进行分类，使用k-means进行聚类，实现他们选择的数据科学管道，对交通堵塞进行建模，应用并行语言功能来求解热方程，并加速机器学习分类系统。
Peachy Parallel Assignments are model assignments for teaching parallel computing concepts. They are competitively selected for being adoptable by other instructors and “cool and inspirational” for students. Thus, they allow instructors to easily add high-quality assignments that will engage students to their classes. This group of Peachy assignments features six new assignments. Students completing them will use k-Nearest Neighbor for classification, cluster using k-means, implement a data science pipeline of their choice, model traffic jams, apply parallel language features to solve the heat equation, and speed up a machine learning classification system.
DOI：
10.1109/ipdpsw.2018.00068
发表时间：
2018
期刊：
2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW
影响因子：
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作者：
Saule, Erik
通讯作者：
Saule, Erik