Abstract

The X10 programming language is intended to ease the programming of scalable concurrent and distributed applications. X10 augments a familiar imperative object-oriented programming model with constructs to support light-weight asynchronous tasks as well as execution across multiple address spaces. A crucial aspect of X10's runtime system is the scheduling of concurrent tasks. Work-stealing schedulers have been shown to efficiently load balance fine-grain divide-and-conquer task-parallel program on SMPs and multicores. But X10 is not limited to shared-memory fork-join parallelism. X10 permits tasks to suspend and synchronize by means of conditional atomic blocks and remote task invocations. In this paper, we demonstrate that work-stealing scheduling principles are applicable to a rich programming language such as X10, achieving performance at scale without compromising expressivity, ease of use, or portability. We design and implement a portable work-stealing execution engine for X10. While this engine is biased toward the efficient execution of fork-join parallelism in shared memory, it handles the full X10 language, especially conditional atomic blocks and distribution. We show that this engine improves the run time of a series of benchmark programs by several orders of magnitude when used in combination with the C++ backend compiler and runtime for X10. It achieves scaling comparable to state-of-the art work-stealing scheduler implementations---the Cilk++ compiler and the Java fork/join framework---despite the dramatic increase in generality.

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