AnyHLS: High-Level Synthesis With Partial Evaluation

Field programmable gate arrays (FPGAs) excel in low power and high throughput computations, but they are challenging to program. Traditionally, developers rely on hardware description languages, such as Verilog or VHDL to specify the hardware behavior at the register-transfer level. High-level synth...

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Veröffentlicht in:IEEE transactions on computer-aided design of integrated circuits and systems 2020-11, Vol.39 (11), p.3202-3214
Hauptverfasser: Ozkan, M. Akif, Perard-Gayot, Arsene, Membarth, Richard, Slusallek, Philipp, Leisa, Roland, Hack, Sebastian, Teich, Jurgen, Hannig, Frank
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Sprache:eng
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Zusammenfassung:Field programmable gate arrays (FPGAs) excel in low power and high throughput computations, but they are challenging to program. Traditionally, developers rely on hardware description languages, such as Verilog or VHDL to specify the hardware behavior at the register-transfer level. High-level synthesis (HLS) raises the level of abstraction but still requires FPGA design knowledge. Programmers usually write pragma-annotated C/C++ programs to define the hardware architecture of an application. However, each hardware vendor extends its own C dialect using its own vendor-specific set of pragmas. This prevents portability across different vendors. Furthermore, pragmas are not first-class citizens in the language. This makes it hard to use them in a modular way or design proper abstractions. In this article, we present AnyHLS, an approach to synthesize FPGA designs in a modular and abstract way. AnyHLS is able to raise the abstraction level of the existing HLS tools by resorting to programming language features such as types and higher order functions as follows. It relies on partial evaluation to specialize and to optimize the user application based on a library of abstractions. Then, vendor-specific HLS code is generated for Intel and Xilinx FPGAs. Portability is obtained by avoiding any vendor-specific pragmas at the source code. In order to validate achievable gains in productivity, a library for the domain of image processing is introduced as a case study, and its synthesis results are compared with several state-of-the-art domain-specific language (DSL) approaches for this domain.
ISSN:0278-0070
1937-4151
DOI:10.1109/TCAD.2020.3012172