SC Conference - Activity Details

Prabhanjan Kambadur  (Indiana University)

Anshul Gupta  (IBM T.J. Watson Research Center)

Amol Ghoting  (IBM T.J. Watson Research Center)

Haim Avron  (Tel-Aviv University)

Andrew Lumsdaine  (Indiana University)

Multicore Task Scheduling

Thursday,  02:00PM - 02:30PM

Room PB255

HPC faces new challenges from paradigm shifts in both hardware and software. The ubiquity of multi-cores, many-cores, and GPGPUs is forcing traditional applications to be parallelized for these architectures. Emerging applications (e.g. in informatics) are placing unique requirements on parallel programming tools that remain unaddressed. Although, of all the available parallel programming models, task parallelism appears to be the most promising in meeting these new challenges, current solutions are inadequate. In this paper, we introduce PFunc, a new library for task parallelism that extends the feature set of current solutions for task parallelism with custom task scheduling, task priorities, task affinities, multiple completion notifications and task groups. These features enable one to naturally parallelize a wide variety of modern HPC applications and to support the SPMD model. We present three case studies: demand-driven DAG execution, frequent pattern mining and sparse iterative solvers to demonstrate the utility of PFunc's new features.

The full paper can be found in the ACM Digital Library and IEEE Computer Society