SHMEM+

Author:

Aggarwal Vikas1,George Alan D.1,Yoon Changil1,Yalamanchili Kishore1,Lam Herman1

Affiliation:

1. University of Florida, Gainesville, FL

Abstract

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+.

Funder

Division of Engineering Education and Centers

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

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1. A Comprehensive Exploration of Languages for Parallel Computing;ACM Computing Surveys;2022-01-18

2. Comparative analysis of coprocessors;Concurrency and Computation: Practice and Experience;2018-09-04

3. A Heterogeneous GASNet Implementation for FPGA-accelerated Computing;Proceedings of the 8th International Conference on Partitioned Global Address Space Programming Models - PGAS '14;2014

4. SCF;ACM Transactions on Reconfigurable Technology and Systems;2012-06

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