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Languages and Compilers for Parallel Computing

LCPC 2015: Languages and Compilers for Parallel Computing pp 106–121Cite as

Asynchronous Nested Parallelism for Dynamic Applications in Distributed Memory

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9519))

Abstract

Nested parallelism is of increasing interest for both expressivity and performance. Many problems are naturally expressed with this divide-and-conquer software design approach. In addition, programmers with target architecture knowledge employ nested parallelism for performance, imposing a hierarchy in the application to increase locality and resource utilization, often at the cost of implementation complexity.

While dynamic applications are a natural fit for the approach, support for nested parallelism in distributed systems is generally limited to well-structured applications engineered with distinct phases of intra-node computation and inter-node communication. This model makes expressing irregular applications difficult and also hurts performance by introducing unnecessary latency and synchronizations. In this paper we describe an approach to asynchronous nested parallelism which provides uniform treatment of nested computation across distributed memory. This approach allows efficient execution while supporting dynamic applications which cannot be mapped onto the machine in the rigid manner of regular applications. We use several graph algorithms as examples to demonstrate our library’s expressivity, flexibility, and performance.

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Acknowledgments

This research is supported in part by NSF awards CNS-0551685, CCF-0702765, CCF-0833199, CCF-1439145, CCF-1423111, CCF-0830753, IIS-0916053, IIS-0917266, EFRI–1240483, RI-1217991, by NIH NCI R25 CA090301-11, by DOE awards DE-AC02-06CH11357, DE-NA0002376, B575363, by Samsung, IBM, Intel, and by Award KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST). This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

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Authors and Affiliations

  1. Parasol Laboratory, Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA

    Ioannis Papadopoulos, Nathan Thomas, Adam Fidel, Dielli Hoxha, Nancy M. Amato & Lawrence Rauchwerger

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  1. Ioannis Papadopoulos
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  2. Nathan Thomas
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  3. Adam Fidel
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  4. Dielli Hoxha
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  5. Nancy M. Amato
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  6. Lawrence Rauchwerger
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Correspondence to Ioannis Papadopoulos .

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Editors and Affiliations

  1. North Carolina State University, Raleigh, North Carolina, USA

    Xipeng Shen

  2. North Carolina State University, Raleigh, North Carolina, USA

    Frank Mueller

  3. North Carolina State University, Raleigh, North Carolina, USA

    James Tuck

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Papadopoulos, I., Thomas, N., Fidel, A., Hoxha, D., Amato, N.M., Rauchwerger, L. (2016). Asynchronous Nested Parallelism for Dynamic Applications in Distributed Memory. In: Shen, X., Mueller, F., Tuck, J. (eds) Languages and Compilers for Parallel Computing. LCPC 2015. Lecture Notes in Computer Science(), vol 9519. Springer, Cham. https://doi.org/10.1007/978-3-319-29778-1_7

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  • DOI: https://doi.org/10.1007/978-3-319-29778-1_7

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