The modern computation and information processing systems shaping our world have become massively distributed, and a fundamental understanding of distributed algorithmics has never been more important. At the same time, despite 40 years of intense study, we often do not have an adequate understanding of the fundamental barriers that rule out the existence of ultra-fast distributed algorithms. This is true even for the most well-studied problems in computer science—including the shortest path, minimum spanning tree, minimum cut, and many other well-known tasks.
In this talk, I will present a high-level overview of a sequence of papers that give a near-complete answer to the above question. Its culmination is the following pie-in-the-sky result called *universal optimality*: for all of the tasks mentioned, there exists a single distributed algorithm that, when run on any communication network G, is provably competitive with the fastest algorithm on G.
The pursuit of universal optimality has led to the development of many new connections between distributed computing and other seemingly unrelated areas of theoretical computer science. Curiously, these connections have been mutually-beneficial and have already led to many breakthroughs not only in distributed computing, but also in the theory of metric embedding, information theory, and oblivious packet routing. I will briefly explore these connections.