Nexus#: A Distributed Hardware Task Manager for Task-Based Programming Models

In the era of multicore systems, it is expected that the number of cores that can be integrated on a single chip will be 3-digit. The key to utilize such a huge computational power is to extract the very fine parallelism in the user program. This is non-trivial for the average programmer, and become...

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Veröffentlicht in:Proceedings - IEEE International Parallel and Distributed Processing Symposium S. 1129 - 1138
Hauptverfasser: Dallou, Tamer, Elhossini, Ahmed, Juurlink, Ben, Engelhardt, Nina
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.05.2015
Schlagworte:
Benchmark testing
data flow
Hardware
hardware support
hardware task scheduler
Multicore processing
parallel programming
Pipelines
Programming
Runtime
Scalability
task graph
task manager
ISSN:1530-2075
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Zusammenfassung:In the era of multicore systems, it is expected that the number of cores that can be integrated on a single chip will be 3-digit. The key to utilize such a huge computational power is to extract the very fine parallelism in the user program. This is non-trivial for the average programmer, and becomes very hard as the number of potential parallel instances increases. Task-based programming models such as OmpSs are promising, since they handle the detection of dependencies and synchronization for the programmer. However, state-of-the-art research shows that task management is not cheap, and introduces a significant overhead that limits the scalability of OmpSs. Nexus# is a hardware accelerator for the OmpSs runtime system, which dynamically monitors dependencies between tasks. It is fully synthesizable in VHDL, and has a distributed task graph model to achieve the best scalability. Supporting tasks with arbitrary number of parameters and any dependency pattern, Nexus# achieves better performance than Nanos, the official OmpSs runtime system, and scales well for the H264dec benchmark with very fine grained tasks, among other benchmarks from the Starbench suite.
ISSN:1530-2075
DOI:10.1109/IPDPS.2015.79