Portable Node-Level Parallelism for the PGAS Model

The Partitioned Global Address Space (PGAS) programming model brings intuitive shared memory semantics to distributed memory systems. Even with an abstract and unifying virtual global address space it is, however, challenging to use the full potential of different systems. Without explicit support by the implementation node-local operations have to be optimized manually for each architecture. A goal of this work is to offer a user-friendly programming model that provides portable performance across systems. In this paper we present an approach to integrate node-level programming abstractions with the PGAS programming model. We describe the hierarchical data distribution with local patterns and our implementation, MEPHISTO, in C++ using two existing projects. The evaluation of MEPHISTO shows that our approach achieves portable performance while requiring only minimal changes to port it from a CPU-based system to a GPU-based one using a CUDA or HIP back-end.

Interoperability strategies for GASPI and MPI in large-scale scientific applications

One of the main hurdles of partitioned global address space (PGAS) approaches is the dominance of message passing interface (MPI), which as a de facto standard appears in the code basis of many applications. To take advantage of the PGAS APIs like global address space programming interface (GASPI) without a major change in the code basis, interoperability between MPI and PGAS approaches needs to be ensured. In this article, we consider an interoperable GASPI/MPI implementation for the communication/performance crucial parts of the Ludwig and iPIC3D applications. To address the discovered performance limitations, we develop a novel strategy for significantly improved performance and interoperability between both APIs by leveraging GASPI shared windows and shared notifications. First results with a corresponding implementation in the MiniGhost proxy application and the Allreduce collective operation demonstrate the viability of this approach.