ABSTRACT Overcoming the Intuition Wall

These are exciting times for computer architecture research. Today there is significant demand to improve the performance and energy-efficiency of emerging, transformative ap-plications which are being hammered out by the hundreds for new compute platforms and usage models. This booming growth of applications and the variety of programming lan-guages used to create them is challenging our ability as architects to rapidly and rigorously characterize these applications. Concurrently, hardware has become more complex with the emergence of accelerators, multicore systems, and heterogeneity caused by further di-vergence between processor market segments. No one architect can now understand all the complexities of many systems and reason about the full impact of changes or new applica-tions. Instead, computer architects must often rely on approximations of software behavior and hardware operation. By using their intuition when necessary and quantitative meth-ods when possible and feasible, architects can actually function. Historically, however, advancement has been achieved most rapidly through deep quantitative understanding and evaluation of ideas and systems. Indeed, computer architecture has a long history as