Power- and Area-optimized Neural Network IC-Design for Academic Education

Florian Frankreiter, A. Breitenreiter, O. Schrape, M. Krstic
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Abstract

A shortage of practically skilled computer science graduates affects academia as well as the industry. Especially when it comes to hardware design and awareness about the complete digital design flow, a lack of qualified personell can hinder the progess of development teams. To address this issue, we will present the design of an integrated circuit (IC) containing a power- and area optimized neural network, enabling know-how development of the students various key skills required for hardware design. This example project, targeting bachelor and master students interested in hardware engineering and artificial intelligence, offers learning potential in various fields and enough room for creative design decisions and detailed discussions. Possible design options and improvements are discussed throughout the paper with focus on their educational aspects.
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面向学术教育的功率和面积优化神经网络集成电路设计
缺乏具有实际技能的计算机科学毕业生不仅影响了学术界,也影响了整个行业。特别是当涉及到硬件设计和对完整数字设计流程的认识时,缺乏合格的人员可能会阻碍开发团队的进展。为了解决这个问题,我们将介绍一个集成电路(IC)的设计,其中包含一个功率和面积优化的神经网络,使学生能够开发硬件设计所需的各种关键技能。这个示例项目针对对硬件工程和人工智能感兴趣的学士和硕士学生,提供了各个领域的学习潜力,并为创造性设计决策和详细讨论提供了足够的空间。可能的设计方案和改进讨论了全文,重点是他们的教育方面。
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