A data parallel programming model based on distributed objects

This paper proposes a data parallel programming model suitable for loosely synchronous, irregular applications. At the core of the model are distributed objects that express non-trivial data parallelism. Sequential objects express independent computations. The goal is to use objects to fold synchronization into data accesses and thus, free the user from concurrency aspects. Distributed objects encapsulate large data partitioned across multiple address spaces. The system classifies accesses to distributed objects as read and write. Furthermore, it uses the access patterns to maintain information about dependences across partitions. The system guarantees inter-object consistency using a relaxed update scheme. Typical access patterns uncover dependences for data on the border between partitions. Experimental results show that this approach is highly usable and efficient.