一种新的计算范式:数据流超级计算的教学经验

N. Trifunovic, Miloš Kotlar, Ognjen Andrić, Petar Trifunovic, S. Stojanovic, M. Cvetanović, Z. Radivojević, Marija Punt, Nenad Korolija, V. Milutinovic
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引用次数: 1

摘要

如果在经验丰富的专业人士面前提出一个新的范式,即使它已经证明了其优越性,也通常会受到抵制。如果一个新的范例已经证明了它的优越性,并且呈现在学生面前,它通常会受到热情的欢迎,特别是如果有工具可以使范例相对容易地使用,如果有一个有用的示例库可供新用户使用,则更是如此。经过一段时间,这些学生成长为经验丰富的专业人士,他们在新的行业岗位上接受新的范式,没有任何阻力。考虑到上述情况,我们为美国和欧洲的大学组织了一系列课程,以Maxeler方法作为实际工作的基准,教授数据流计算范式。这些课程分为三个不同的层次:(A)一个小时的演示,然后是另一个小时的编程模型,以及一个小时的工具实践,(B)一个经过认证的全天短期课程,学生可以在他们的成绩单中使用,作为文凭的补充,(C)一个学期的课程,学生可以将1、2或3个学分作为毕业要求。不同的表达层次要求不同的表达方式,在传播领域产生不同的结果。以下是A组10所大学、B组10所大学和c组10所大学的结果。在适当的情况下,这些结果都有统计数据支持。
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Experiences in the teaching of a new computing paradigm: DataFlow supercomputing
If a new paradigm is presented before experienced professionals, even if it already demonstrates superiority, the presentation is typically received with resistance. If a new paradigm already demonstrates superiority, and it is presented before students, it is typically received with enthusiasm, especially if tools are available that enable the paradigm to be utilized with a relative ease, and even more if a library of useful examples is at the disposal of new users. Over a period of time, these students grow into experienced professionals who accept the new paradigm, at their new industrial posts, without any resistance. With the above in mind, a series of courses was organized for universities in the USA and Europe, to teach the data flow computing paradigm, using the Maxeler approach as the baseline for practical work. The courses were organized on three different levels: (A) One-hour presentations, followed by another hour about the programming model, and a hands-on hour with tools, (B) A certified full-day short-course that students could use in their transcripts as a diploma supplement, and (C) A one-semester course for 1, 2, or 3 credits that students could use as a graduation requirement. Different presentation levels require different methods of presentation and produce different results in the dissemination domain. These results are here presented for 10 universities in the group A, 10 in the group B, and 10 in the group C. Where appropriate, the findings are backed with statistics data.
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