The end of Moore's Law and Dennard Scaling has combined with advances in agile hardware design to foster a golden age of domain-specific acceleration. However, this new frontier of computing opportunities is not without pitfalls. As computer architects approach unfamiliar domains, we have seen common themes emerge in the challenges that can hinder progress in the development of useful acceleration. In this work, we present the Magnificent Seven Challenges in domain-specific accelerator design that can guide adventurous architects to contribute meaningfully to novel application domains. Although these challenges appear across domains ranging from ML to genomics, we examine them through the lens of autonomous systems as a motivating example in this work. To that end, we identify opportunities for the path forward in a successful domain-specific accelerator design from these challenges.

翻译：摩尔定律与登纳德缩放定律的终结，结合敏捷硬件设计的进步，共同催生了领域专用加速器的黄金时代。然而，这一计算领域的新前沿并非没有陷阱。随着计算机体系结构研究者涉足不熟悉的领域，我们发现阻碍有效加速器开发的挑战中反复出现一些共同主题。在本工作中，我们提出了领域专用加速器设计的"七大挑战"，以引导勇于探索的体系结构研究者为新颖应用领域做出有意义的贡献。尽管这些挑战出现在从机器学习到基因组学等多个领域，但我们在工作中以自主系统作为典型案例来审视它们。为此，我们从这些挑战中识别出成功设计领域专用加速器的未来发展机遇。