The overwhelming wealth of parallelism exposed by Extreme-scale computing is rekindling the interest for finegrain multithreading, particularly at the intranode level. Indeed, popular parallel programming models, such as OpenMP, are integrating fine-grain tasking in their newest standards. Yet, classical coarse-grain constructs are still largely preferred, as they are considered simpler to express parallelism. In this paper, we present a Multigrain Parallel Programming environment that allows programmers to use these well-known coarse-grain constructs to generate a fine-grain multithreaded application to be run on top of a fine-grain event-driven program execution model. Experimental results with four scientific benchmarks (Graph500, NAS Data Cube, NWChem-SCF, and ExMatEx's CoMD) show that fine-grain applications generated by and run on our environment are competitive and even outperform their OpenMP counterparts, especially for data-intensive workloads with irregular and dynamic parallelism, reaching speedups as high as 2.6x for Graph500 and 50x for NAS Data Cube.

The recent evolution in hardware landscape, aimed at producing high-performance computing systems capable of reaching extreme-scale performance, has reignited the interest in fine-grain multithreading, particularly at the intranode level. Indeed, popular parallel programming environments, such as OpenMP, which features a simple interface for the parallelization of programs, are now incorporating fine-grain constructs. However, since coarse-grain directives are still heavily used, the OpenMP runtime is forced to support both coarse- and fine-grain models of execution, potentially reducing the advantages obtained when executing an application in a fully fine-grain environment. To evaluate the type of applications that benefit from executing in a unified fine-grain program execution model, this article presents amultigrain parallel programming environmentfor the generation of fine-grain multithreaded applications from programs featuring OpenMP’s API, allowing OpenMP programs to be run on top of a fine-grain event-driven program execution model. Experimental results with five scientific benchmarks show that fine-grain applications, generated by and run on our environment with two runtimes implementing a fine-grain event-driven program execution model, are competitive and can outperform their OpenMP counterparts, especially for data-intensive workloads with irregular and dynamic parallelism, reaching speedups as high as 2.6× for Graph500 and 51× for NAS Data Cube.