Abstract

Today’s storage landscape offers a deep and heterogeneous stack of technologies that promises to meet even the most demanding dataintensive workload needs. The diversity of technologies, however, presents a challenge. Parts of it are not controlled directly by the application, e.g., the cache layers, and the parts that are controlled, often require the programmer to deal with very different transfer mechanisms, such as disk and network APIs. Combining these different abstractions properly requires great skill, and even so, expert-written programs can lead to sub-optimal utilization of the storage stack and present performance unpredictability. In this paper, we propose to combat these issues with a new programming abstraction called Data Pipes. Data pipes offer a new API that can express data transfers uniformly, irrespective of the source and destination data placements. By doing so, they can orchestrate how data moves over the different layers of the storage stack explicitly and fluidly. We suggest a preliminary implementation of Data Pipes that relies mainly on existing hardware primitives to implement data movements. We evaluate this implementation experimentally and comment on how a full version of Data Pipes could be brought to fruition.