Toward High Performance Computing Education
Toward High Performance Computing Education
复制标题
迈向高性能计算教育
DOI：
10.1145/3341525.3394989
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Rahimi, Shahram
中科院分区：
文献类型：
--
作者：
Raj, Rajendra K.;Romanowski, Carol J.;Aly, Sherif G.;Becker, Brett A.;Chen, Juan;Ghafoor, Sheikh;Giacaman, Nasser;Gordon, Steven I.;Izu, Cruz;Rahimi, Shahram
高性能计算（HPC）是以极高的速度处理数据和执行复杂计算的能力。当前的HPC平台可以实现每秒万亿次计算的数量级的计算，而百万分之一的计算即将到来。过去三十年，不同科学、工程和商业领域对高性能计算的使用大幅增加，例如基因组测序、预测气候变化、设计现代空气动力学或建立客户偏好。尽管HPC已经很好地融入了生物信息学等科学课程，但对于大多数计算程序来说，情况并非如此。该工作组将探讨HPC如何进入计算机科学教育，从本科到研究生水平。该小组将解决旨在调查主题的研究问题，例如识别和处理阻碍在教育环境中采用HPC的障碍，如何将HPC纳入各种课程，以及如何利用HPC来增强应用批判性思维和解决问题的技能。四项交付成果包括：（1）核心HPC教育概念目录，（2）满足当代计算需求的HPC课程，例如人工智能，网络分析，数据科学和工程或物联网，（3）实施HPC课程的可能基础设施，以及（4）对CC2020项目的HPC相关反馈。
High Performance Computing (HPC) is the ability to process data and perform complex calculations at extremely high speeds. Current HPC platforms can achieve calculations on the order of quadrillions of calculations per second with quintillions on the horizon. The past three decades witnessed a vast increase in the use of HPC across different scientific, engineering and business communities, for example, sequencing the genome, predicting climate changes, designing modern aerodynamics, or establishing customer preferences. Although HPC has been well incorporated into science curricula such as bioinformatics, the same cannot be said for most computing programs. This working group will explore how HPC can make inroads into computer science education, from the undergraduate to postgraduate levels. The group will address research questions designed to investigate topics such as identifying and handling barriers that inhibit the adoption of HPC in educational environments, how to incorporate HPC into various curricula, and how HPC can be leveraged to enhance applied critical thinking and problem solving skills. Four deliverables include: (1) a catalog of core HPC educational concepts, (2) HPC curricula for contemporary computing needs, such as in artificial intelligence, cyberanalytics, data science and engineering, or internet of things, (3) possible infrastructures for implementing HPC coursework, and (4) HPC-related feedback to the CC2020 project.
登录
查看更多内容
DOI：
10.1007/978-3-030-16205-4
发表时间：
2018
期刊：
Communications in Computer and Information Science
影响因子：
--
作者：
Suzanne Lun
通讯作者：
Suzanne Lun
DOI：
10.1145/1971681.1971689
发表时间：
2010-06
期刊：
--
影响因子：
--
作者：
Richard A. Brown;E. Shoop;Joel C. Adams;C. Clifton;M. Gardner;M. Haupt;Peter Hinsbeeck
通讯作者：
Richard A. Brown;E. Shoop;Joel C. Adams;C. Clifton;M. Gardner;M. Haupt;Peter Hinsbeeck
DOI：
10.1145/3344429.3372503
发表时间：
2019
期刊：
Proceedings of the Working Group Reports on Innovation and Technology in Computer Science Education
影响因子：
--
作者：
Raj, Rajendra K.;Parrish, Allen;Impagliazzo, John;Romanowski, Carol J.;Aly, Sherif G.;Bennett, Casey C.;Davis, Karen C.;McGettrick, Andrew;Pereira, Teresa Susana;Sundin, Lovisa
通讯作者：
Sundin, Lovisa
网络安全：可视化分析如何释放洞察力
DOI：
10.1145/2487575.2491132
发表时间：
2013
期刊：
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
影响因子：
--
作者：
R. Marty
通讯作者：
R. Marty
呼吁采取行动，培养高性能计算劳动力
影响因子：
2.1
作者：
Scott A. Lathrop
通讯作者：
Scott A. Lathrop