Run-time Data Distribution for Block-Structured Applications on Distributed Memory Computers

In many scientific applications running on parallel computers, efficient data decompositions exhibit a block structure which can be regular or irregular. We present a run-time strategy for both regular and irregular block-structured applications which provides a three-stage mapping including alignment, first-class decomposition objects, and block data movement. We have implemented this strategy using a small set of primitive operations, and present these along with performance results. In contrast to data parallel Fortran dialects, our system executes completely at run-time and supports coarse-grained user-defined data decompositions. 1 Introduction It is well-known that on distributed memory parallel computers, the distribution of data across processors can have a substantial impact on a program's performance. Under the message-passing programming model, the programmer must manage all aspects of data distribution by hand. Programming languages and run-time libraries that manage the l..