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.

分区全局地址空间 (PGAS) 编程模型为分布式内存系统带来了直观的共享内存语义。然而，即使拥有抽象且统一的虚拟全局地址空间，充分利用不同系统的潜力也充满挑战。如果没有实现的明确支持，则必须针对每个架构手动优化节点本地操作。这项工作的目标是提供一个用户友好的编程模型，提供跨系统的可移植性能。在本文中，我们提出了一种将节点级编程抽象与 PGAS 编程模型集成的方法。我们使用两个现有项目在 C++ 中描述了具有本地模式的分层数据分布和我们的实现 MEPHISTO。 MEPHISTO 的评估表明，我们的方法实现了可移植性能，同时只需进行最小的更改即可将其从基于 CPU 的系统移植到使用 CUDA 或 HIP 后端的基于 GPU 的系统。