Embedding a hardware description language in a functional meta-programming language

General purpose functional languages such as Haskell, have been widely used as host languages for the embedding of domain specific languages. In particular, various hardware description languages have been successfully embedded in Haskell and other functional languages. More recently, meta-programming languages have also started being used for the embedding of such languages, where the meta-language features allow us to access the structure of data objects in a shallow-style embedding, while retaining the characteristics of a deep-embedding. In this paper, we discuss the application of meta-functional languages for the embedding of a hardware description language, based on reFLect, a functional meta-language which provides an alternative approach for embedding a hardware description language by means of built-in reflection features. Through the use of code quotation and pattern matching, we use reFLect to build a framework through which we can access the structure of our circuits by means of reflection.peer-reviewe

Autotuning the Intel HLS Compiler using the Opentuner Framework

High level synthesis (HLS) tools can be used to improve design flow and decrease verification times for field programmable gate array (FPGA) and application specific integrated circuit (ASIC) design. The Intel HLS Compiler is a high level synthesis tool that takes in untimed C/C++ as input and generates production-quality register transfer level (RTL) code that is optimized for Intel FPGAs. The translation does, however, require multiple iterations and manual optimizations to get comparable synthesized results to that of a solution written in a hardware descriptive language. The synthesis results can vary greatly based upon coding style and optimization techniques, and typically require an in-depth knowledge of FPGAs to fully optimize the translation which limits the audience of the tool. The extra abstraction that the C/C++ source code presents can also make it difficult to meet more specific design requirements; this includes designs to meet specific resource usage or performance based metrics. To improve the quality of results generated by the Intel HLS Compiler without a manual iterative process that requires an in-depth knowledge of FPGAs, this research proposes a method of automating some of the optimization techniques that improve the synthesized design through an autotuning process. The proposed approach utilizes the PyCParser library to parse C source files and the OpenTuner Framework to autotune the synthesis to provide a method that generates results that better meet the needs of the designer's requirements through lower FPGA resource usage or increased design performance. Such functionality is not currently available in Intel's commercial tools. The proposed approach was tested with the CHStone Benchmarking Suite of C programs as well as a standard digital signal processing finite impulse response filter. The results show that the commercial HLS tool can be automatically autotuned through placeholder injection using a source parsing tool for C code and using the OpenTuner Framework to autotune the results. For designs that are small in nature and include conducive structures to be autotuned, the results indicate resource usage reductions and/or performance increases of up to 40% as compared to the default Intel HLS Compiler results. The method developed in this research also allows additional design targets to be specified through the autotuner for consideration in the synthesized design which can yield results that are better matched to a design's requirements

Access to circuit generators in embedded hdls

General purpose functional languages have been widely used as host languages for the embedding of domain specific languages, especially hardware description languages. The embedding approach provides various abstraction techniques, enabling the description of generators for whole families of circuits, in particular parameterised regular circuits. The two-stage language setting that is achieved by means of embedding, provides a means to reason about the generated circuits as data objects within the host language. Nonetheless, these circuit objects lack information about their generators, or about the manner in which these where generated, which can be used for placement and analysis. In this paper, we use reFLect as a functional language with reflection features, to enable us not only to access the circuits, but also the circuit generators. Through the use of code quotation and pattern matching, we propose a framework through which we can access the structure of the circuit in terms of nested blocks that map the generation flow that was followed by the generator.peer-reviewe

FPGA dynamic and partial reconfiguration : a survey of architectures, methods, and applications

Dynamic and partial reconfiguration are key differentiating capabilities of field programmable gate arrays (FPGAs). While they have been studied extensively in academic literature, they find limited use in deployed systems. We review FPGA reconfiguration, looking at architectures built for the purpose, and the properties of modern commercial architectures. We then investigate design flows, and identify the key challenges in making reconfigurable FPGA systems easier to design. Finally, we look at applications where reconfiguration has found use, as well as proposing new areas where this capability places FPGAs in a unique position for adoption