"Computing performance doubles every couple of years" is the popular re-phrasing of Moore's Law, which describes the 500,000 – fold increase in the number of transistors on modern computer chips. But what impact has this 50 – year expansion of the technological frontier of computing had on the productivity of firms? This paper focuses on the surprise change in chip design in the mid-2000s, when Moore's Law faltered. No longer could it provide ever-faster processors, but instead it provided multicore ones with stagnant speeds. Using the asymmetric impacts from the changeover to multicore, this paper shows that firms that were ill-suited to this change because of their software usage were much less advantaged by later improvements from Moore's Law.

The miniaturization of semiconductor transistors has driven the growth in computer performance for more than 50 years. As miniaturization approaches its limits, bringing an end to Moore's law, performance gains will need to come from software, algorithms, and hardware. We refer to these technologies as the "Top" of the computing stack to distinguish them from the traditional technologies at the "Bottom": semiconductor physics and silicon-fabrication technology. In the post-Moore era, the Top will provide substantial performance gains, but these gains will be opportunistic, uneven, and sporadic, and they will suffer from the law of diminishing returns. Big system components offer a promising context for tackling the challenges of working at the Top.

The general-purposeness of today's computers comes from technical achievements, but also from a mutually-reinforcing economic cycle, where product improvement and market growth fuel each other. This article argues that technological and economic forces are now pushing computing away from being general purpose and towards specialization. This fragmentation process, driven by the breakdowns in Moore's Law and Dennard Scaling, has already begun and threatens to divide computing into 'fast lane' applications that get powerful specialized processors and 'slow lane' applications that get stuck using general purpose processors whose progress fades.