Providing a supported online course on parallel computing

S. Gordon, Jay Alameda, J. Demmel, R. Carbunescu, Susan Mehringer
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引用次数: 2

Abstract

Learning the principles of computational modeling and parallel computing requires more than a short workshop. Workshops generally run from a few hours to a few days and are therefore limited in the amount of material that can be covered. In addition, it is more difficult for participants to retain large amounts of new material under the time pressures of a workshop. Deeper understanding of such complex materials can come from more traditional academic courses. Yet, many institutions either lack the expertise or the curriculum flexibility to offer such courses. In the spring of 2013 we offered the equivalent of a full semester course entitled Applications of Parallel Computing as an open, online course in an effort to address these issues. The course was offered over a period of thirteen weeks using materials captured from the University of California Berkeley course CS267. Enrollment was initially limited to 345 students. Creating and implementing the course involved decisions in several areas: design of the instructional materials, creating an environment to run programming assignments, support mechanisms for the large number of students taking the course, and automatic grading of assignments. In this session, we will present a summary of the experience in addressing these questions along with an evaluation of the course outcomes.
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提供支持并行计算的在线课程
学习计算建模和并行计算的原理需要的不仅仅是一个简短的研讨会。讲习班通常从几个小时到几天不等,因此可以涵盖的材料数量有限。此外,在工作坊的时间压力下,参与者很难保留大量的新材料。对这些复杂材料的更深入理解可以从更传统的学术课程中获得。然而,许多机构要么缺乏专业知识,要么缺乏提供此类课程的课程灵活性。为了解决这些问题,我们在2013年春季开设了一门相当于一整个学期的课程,名为《并行计算应用》(Applications of Parallel Computing),这是一门开放的在线课程。该课程为期13周,使用的材料来自加州大学伯克利分校的CS267课程。入学人数最初限制在345名学生。创建和实施课程涉及几个方面的决策:教学材料的设计,创建运行编程作业的环境,为大量选修课程的学生提供支持机制,以及作业的自动评分。在本节课中,我们将总结解决这些问题的经验,并对课程成果进行评估。
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