My approach to research has been driven by a couple of adages: "Necessity is the mother of invention" and "Research has to be good for something before it is good for everything." Over my career the aim of my research has been to enable system designers to fully utilize the capabilities that silicon manufacturing has provided them. After many years of working on the problem of how to design Integrated Circuits (i.e. Electronic Design Automation), I turned my focus to how to program Integrated Circuits, particularly on-chip multiprocessor systems. Since joining Berkeley I have been exploring applications of “personal high-performance computing” enabled by these on-chip multiprocessors systems. In particular my group has focused on applications in computer-vision, speech recognition, multimedia analytics, and computational finance. As Deep Neural Networks have proved successful at providing state-of-the-art solutions to all of these problems, I am now focusing my entire research efforts on the problems of providing state-of-the-art solutions to the training and deployment of Deep Neural Networks.