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Source-to-Source Optimization for HLS

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Abstract

This chapter describes the source code optimization techniques and automation tools for FPGA design with high-level synthesis (HLS) design flow. HLS has lifted the design abstraction from RTL to C/C++, but in practice extensive source code rewriting is often required to achieve a good design using HLS—especially when the design space is too large to determine the proper design options in advance. In addition, this code rewriting requires not only the knowledge of hardware microarchitecture design, but also familiarity with the coding style for the high-level synthesis tools. Automatic source-to-source transformation techniques have been applied in software compilation and optimization for a long time. They can also greatly benefit the FPGA accelerator design in a high-level synthesis design flow. In general, source-to-source optimization for FPGA will be much more complex and challenging than that for CPU software because of the much larger design space in microarchitecture choices combined with temporal/spatial resource allocation. The goal of source-to-source transformation is to reduce or eliminate the design abstraction gap between software/algorithm development and existing HLS design flows. This will enable the fully automated FPGA design flows for software developers, which is especially important for deploying FPGAs in data centers, so that many software developers can efficiently use FPGAs with minimal effort for acceleration.

This work was performed while the author J. Cong served as the Chief Scientific Advisor of Falcon Computing Solutions Inc.

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Acknowledgements

This work is partially supported by the National Science Foundation Small Business Innovation Research (SBIR) Grant No. 1520449 for project entitled “Customized Computing for Big Data Applications”.

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Authors and Affiliations

  1. Falcon Computing Solutions, Inc., Los Angeles, CA, USA

    Jason Cong, Muhuan Huang, Peichen Pan, Yuxin Wang & Peng Zhang

  2. Computer Science Department, University of California, Los Angeles, CA, USA

    Jason Cong

Authors
  1. Jason Cong
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  2. Muhuan Huang
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  3. Peichen Pan
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  4. Yuxin Wang
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  5. Peng Zhang
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Corresponding author

Correspondence to Jason Cong .

Editor information

Editors and Affiliations

  1. The University of Manchester, Manchester, United Kingdom

    Dirk Koch

  2. Erlangen-NĂĽrnberg, Friedrich-Alexander University, Erlangen, Germany

    Frank Hannig

  3. Dept. of Computer Science, Hardware/Software Co-Design, Erlangen, Germany

    Daniel Ziener

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Cong, J., Huang, M., Pan, P., Wang, Y., Zhang, P. (2016). Source-to-Source Optimization for HLS. In: Koch, D., Hannig, F., Ziener, D. (eds) FPGAs for Software Programmers. Springer, Cham. https://doi.org/10.1007/978-3-319-26408-0_8

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  • DOI: https://doi.org/10.1007/978-3-319-26408-0_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26406-6

  • Online ISBN: 978-3-319-26408-0

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