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Mitigating synchronization bottlenecks in high-performance actor-model-based software
DescriptionBulk synchronous programming (in distributed-memory systems) and the
fork-join pattern (in shared-memory systems) are often used for
problems where independent processes must periodically
synchronize. Frequent synchronization can greatly undermine the
performance of software designed to solve such problems. We use
the actor model of concurrent computing to balance the load of
hundreds of thousands of short-lived tasks, and mitigate
synchronization bottlenecks by buffering communication via actor
batching. The actor model is becoming increasingly popular in scientific and
high-performance computing because it can handle heterogeneous tasks
and computing environments with enhanced programming flexibility and
ease relative to conventional paradigms like MPI. For a hydrologic
simulation of continental North America with over 500,000 elements,
the proposed buffering approach is approximately 4 times faster than
no buffering, outperforms MPI on single and multiple nodes, and
remains competitive with OpenMP on a single node and MPI+OpenMP on
multiple nodes.
Event Type
Workshop
TimeSunday, 17 November 202411:50am - 12:10pm EST
LocationB306
Tags
Heterogeneous Computing
Parallel Programming Methods, Models, Languages and Environments
PAW-Full
Task Parallelism
Registration Categories
W