Portable Inter-workgroup Barrier Synchronisation for GPUs

2016_OOPSLA_sdbgr screenshot

Abstract

Despite the growing popularity of GPGPU programming, there is not yet a portable and formally-specified barrier that one can use to synchronise across workgroups. Moreover, the occupancy-bound execution model of GPUs breaks assumptions inherent in traditional software execution barriers, exposing them to deadlock. We present an occupancy discovery protocol that dynamically discovers a safe estimate of the occupancy for a given GPU and kernel, allowing for a starvation-free (and hence, deadlock-free) inter-workgroup barrier by restricting the number of workgroups according to this estimate. We implement this idea by adapting an existing, previously non-portable, GPU inter-workgroup barrier to use OpenCL 2.0 atomic operations, and prove that the barrier meets its natural specification in terms of synchronisation. We assess the portability of our approach over eight GPUs spanning four vendors, comparing the performance of our method against alternative methods. Our key findings include: (1) the recall of our discovery protocol is nearly 100%; (2) runtime comparisons vary substantially across GPUs and applications; and (3) our method provides portable and safe inter-workgroup synchronisation across the applications we study.

Citation

Tyler Sorensen, Alastair F. Donaldson, Mark Batty, Ganesh Gopalakrishnan, Zvonimir Rakamaric
Portable Inter-workgroup Barrier Synchronisation for GPUs
Proceedings of the ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA), 39--58, 2016.

BibTeX

@inproceedings{2016_OOPSLA_sdbgr,
  title = {Portable Inter-workgroup Barrier Synchronisation for GPUs},
  author = {Tyler Sorensen and Alastair F. Donaldson and Mark Batty and Ganesh Gopalakrishnan and Zvonimir Rakamaric},
  booktitle = {Proceedings of the ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA)},
  publisher = {ACM},
  pages = {39--58},
  year = {2016}
}