  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.
