Abstract
The Message Passing Interface (MPI) standard continues to dominate the landscape of parallel computing as the de facto API for writing large-scale scientific applications. But the critics argue that it is a low-level API and harder to practice than shared memory approaches. This paper addresses the issue of programming productivity by proposing a high-level, easy-to-use, and efficient programming API that hides and segregates complex low-level message passing code from the application specific code. Our proposed API is inspired by communication patterns found in Gadget-2, which is an MPI-based parallel production code for cosmological N-body and hydrodynamic simulations. In this paper-we analyze Gadget-2 with a view to understanding what high-level Single Program Multiple Data (SPMD) communication abstractions might be developed to replace the intricate use of MPI in such an irregular application-and do so without compromising the efficiency. Our analysis revealed that the use of low-level MPI primitives-bundled with the computation code-makes Gadget-2 difficult to understand and probably hard to maintain. In addition, we found out that the original Gadget-2 code contains a small handful of-complex and recurring-patterns of message passing. We also noted that these complex patterns can be reorganized into a higher-level communication library with some modifications to the Gadget-2 code. We present the implementation and evaluation of one such message passing pattern (or schedule) that we term Collective Asynchronous Remote Invocation (CARI). As the name suggests, CARI is a collective variant of Remote Method Invocation (RMI), which is an attractive, high-level, and established paradigm in distributed systems programming. The CARI API might be implemented in several ways-we develop and evaluate two versions of this API on a compute cluster. The performance evaluation reveals that CARI versions of the Gadget-2 code perform as well as the original Gadget-2 code but the level of abstraction is raised considerably.