Scalable communication protocols for dynamic sparse data exchange

Abstract

Many large-scale parallel programs follow a bulk synchronous parallel (BSP) structure with distinct computation and communication phases. Although the communication phase in such programs may involve all (or large numbers) of the participating processes, the actual communication operations are usually sparse in nature. As a result, communication phases are typically expressed explicitly using point-to-point communication operations or collective operations. We define the dynamic sparse data-exchange (DSDE) problem and derive bounds in the well known LogGP model. While current approaches work well with static applications, they run into limitations as modern applications grow in scale, and as the problems that are being solved become increasingly irregular and dynamic.