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SLAW: a scalable locality-aware adaptive work-stealing scheduler for multi-core systems
Proceedings of the 15th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
Flexible architectural support for fine-grain scheduling
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Lifeline-based global load balancing
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A high-level framework for distributed processing of large-scale graphs
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HipG: parallel processing of large-scale graphs
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A work-stealing scheduler for X10's task parallelism with suspension
Proceedings of the 17th ACM SIGPLAN symposium on Principles and Practice of Parallel Programming
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Work-stealing without the baggage
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Scheduling parallel programs by work stealing with private deques
Proceedings of the 18th ACM SIGPLAN symposium on Principles and practice of parallel programming
DANBI: dynamic scheduling of irregular stream programs for many-core systems
PACT '13 Proceedings of the 22nd international conference on Parallel architectures and compilation techniques
Energy-efficient work-stealing language runtimes
Proceedings of the 19th international conference on Architectural support for programming languages and operating systems
GLB: lifeline-based global load balancing library in x10
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Friendly barriers: efficient work-stealing with return barriers
Proceedings of the 10th ACM SIGPLAN/SIGOPS international conference on Virtual execution environments
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Solving large, irregular graph problems efficiently is challenging. Current software systems and commodity multiprocessors do not support fine-grained, irregular parallelism well. We present XWS, the X10 Work Stealing framework, an open-source runtime for the parallel programming language X10 and a library to be used directly by application writers. XWS extends the Cilk work-stealing framework with several features necessary to efficiently implement graph algorithms, viz., support for improperly nested procedures, global termination detection, and phased computation. We also present a strategy to adaptively control the granularity of parallel tasks in the work-stealing scheme, depending on the instantaneous size of the work queue. We compare the performance of the XWS implementations of spanning tree algorithms with that of the hand-written C and Cilk implementations using various graph inputs. We show that XWS programs (written in Java) scale and exhibit comparable or better performance.