SHMEM+: A Multilevel-PGAS Programming Model for Reconfigurable Supercomputing

Vikas A. Aggarwal

doi:10.1145/2000832.2000838

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SHMEM+: A Multilevel-PGAS Programming Model for Reconfigurable Supercomputing

2011-08-22

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Vikas A. Aggarwal *

Alan D. George

Changil Yoon

Kishore K. Yalamanchili

Herman Lam

DOI：10.1145/2000832.2000838

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Abstract

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Reconfigurable Computing (RC) systems based on FPGAs are becoming an increasingly attractive solution to building parallel systems of the future. Applications targeting such systems have demonstrated superior performance and reduced energy consumption versus their traditional counterparts based on microprocessors. However, most of such work has been limited to small system sizes. Unlike traditional HPC systems, lack of integrated, system-wide, parallel-programming models and languages presents a significant design challenge for creating applications targeting scalable, reconfigurable HPC systems. In this article, we extend the traditional Partitioned Global Address Space (PGAS) model to provide a multilevel integration of memory, which simplifies development of parallel applications for such systems and improves developer productivity. The new multilevel-PGAS programming model captures the unique characteristics of reconfigurable HPC systems, such as the existence of multiple levels of memory hierarchy and heterogeneous computation resources. Based on this model, we extend and adapt the SHMEM communication library to become what we call SHMEM+, the first known SHMEM library enabling coordination between FPGAs and CPUs in a reconfigurable, heterogeneous HPC system. Applications designed with SHMEM+ yield improved developer productivity compared to current methods of multidevice RC design and exhibit a high degree of portability. In addition, our design of SHMEM+ library itself is portable and provides peak communication bandwidth comparable to vendor-proprietary versions of SHMEM. Application case studies are presented to illustrate the advantages of SHMEM+.

Keywords:

Design

Languages

Performance

Reconfigurable computing

parallel programming

programming language

programming model

productivity

portability

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