Itoyori: Reconciling Global Address Space and Global Fork-Join Task Parallelism

This paper introduces Itoyori, a task-parallel runtime system designed to tackle the challenge of scaling task parallelism (more specifically, nested fork-join parallelism) beyond a single node. The partitioned global address space (PGAS) model is often employed in task-parallel systems, but naively combining them can lead to poor performance due to fine-grained and redundant remote memory accesses. Itoyori addresses this issue by automatically caching global memory accesses at runtime, enabling efficient cache sharing among parallel tasks running on the same processor. As a real-world case study, we ported an existing task-parallel implementation of the Fast Multipole Method (FMM) to distributed memory with Itoyori and achieved a 7.5× speedup when scaled from a single node to 12 nodes and up to 6.0× faster performance than without caching. This study demonstrates that global-view fork-join programming can be made practical and scalable, while requiring minimal changes to the shared-memory code.