Extreme-scale simulations and experiments can generate large amounts of data, whose volume can exceed the compute and/or storage capacity at the simulation or experimental facility. With the emergence of ultra-high-speed networks, researchers are considering pipelined approaches in which data are passed to a remote facility for analysis. Here we examine an extreme-scale cosmology simulation that, when run on a large fraction of a leadership computer, generates data at a rate of one petabyte per elapsed day. Writing those data to disk is inefficient and impractical, and in situ analysis poses its own difficulties. Thus we implement a pipeline in which data are generated on one supercomputer and then transferred, as they are generated, to a remote supercomputer for analysis. We use the Swift scripting language to instantiate this pipeline across Argonne National Laboratory and the National Center for Supercomputing Applications, which are connected by a 100 Gb/s network; and we demonstrate that by using the Globus transfer service we can achieve a sustained rate of 93 Gb/s over a 24-hour period, thus attaining our performance goal of one petabyte moved in 24 h. This paper describes the methods used and summarizes the lessons learned in this demonstration.